Word2vec & Chatbots 2018


Notes:

In 2018, the number of academic papers on word2vec and chatbots doubled from the previous year.

Resources:

Wikipedia:

See also:

100 Best GitHub: N-gram | 100 Best GitHub: Natural Language


Developing Chatbots
NK Manaswi – Deep Learning with Applications Using Python, 2018 – Springer
… DBPedia vectors (wiki2vec). 1000. -. -. Word2Vec. BoW, 10. Idio. Building the Response. Reponses are another important part of chatbots. Based on how a chatbot replies, a user may get attracted to it. Whenever a chatbot is made, one thing that should be kept in mind is its users …

User adaptive chatbot for mitigating depression
P Kataria, K Rode, A Jain, P Dwivedi… – International Journal of …, 2018 – acadpubl.eu
… 3 Proposed Methodology Chatbots tend to fail when encountered with an unknown state- ment … Another study used word2vec to generate natural sounding phrases[12] … Chatbot Using a Knowl- edge in Database: Human-to-Machine Conversation Mod- eling …

Improving Matching Models with Contextualized Word Representations for Multi-turn Response Selection in Retrieval-based Chatbots
C Tao, W Wu, C Xu, Y Feng, D Zhao, R Yan – arXiv preprint arXiv …, 2018 – arxiv.org
… Existing approaches to building a chatbot include generation-based meth- ods (Shang et al … this work, we study multi-turn response selec- tion for retrieval-based chatbots, because retrieval … pre-trained on large-scale unlabeled text with algorithms such as Word2Vec (Mikolov et al …

Building a Question-Answering Chatbot using Forum Data in the Semantic Space
K Mrini, M Laperrouza, P Dillenbourg – 2018 – infoscience.epfl.ch
… When a user enters a request, the chatbot has already loaded the word2vec model and com … The answers given by the chatbot remain at least somewhat within context, and the chatbot can pro … Building chatbots from forum data: Model selection using question answering metrics …

Modern Chatbot Systems: A Technical Review
AS Lokman, MA Ameedeen – Proceedings of the Future Technologies …, 2018 – Springer
… Referring to Table 1, it is clear that modern chatbots are 90% similar in term of … Word embedding has emerged to become prominent in modern chatbot system architecture. Word2Vec and GloVe are perhaps the two most used techniques in generating WE for chatbot system …

Al-Chatbot: Elderly Aid
G Tascini – Proceedings on the International Conference on …, 2018 – search.proquest.com
… Current chatbots are in difficulty facing these tasks and overcome it by introducing Deep L … To this aim we can use the before seen approach of a Word2Vec model … Recognition and Speech Synthesis are indispensable steps for completing user interaction with chatbot, These are …

Safebot: A Safe Collaborative Chatbot
M Chkroun, A Azaria – Workshops at the Thirty-Second AAAI Conference …, 2018 – aaai.org
… eg AIML (Wallace 2003)) or rely on data mined from different sources that were never intended to be a source for chatbots … word2vec explained: de- riving mikolov et al.’s negative-sampling word-embedding method … Extracting chatbot knowledge from online discussion forums …

Domain-Specific Reduction of Language Model Databases: Overcoming Chatbot Implementation Obstacles
NJ Kaimakis, S Breck, BD Nye, DM Davis – modsimworld.com
… The proliferation and practical use of chatbots depends on the ability of users to conversationally … A chatbot must be able to understand and respond to a variety of unique user … analyzes two methods for reducing language models, using the Google News Word2vec model as an …

Embedding Individual Table Columns for Resilient SQL Chatbots
B Petrovski, I Aguado, A Hossmann… – arXiv preprint arXiv …, 2018 – arxiv.org
… Using this corpus we train a word2vec model with the Gensim toolkit ( ?Rehurek and Sojka, 2010) … In this paper, we proposed a new approach to build SQL chatbots without relying on the … Even with these changes, there is still room for improvement in the SQL chatbot area …

PESUBot: An Empathetic Goal Oriented Chatbot
HV Kumar, J Nagaraj, M Irfan… – … on Advances in …, 2018 – ieeexplore.ieee.org
… Also, an utterance embedding of each word in the input is derived, using a pre-built model such as Google’s word2vec model [5]. Next, the entity extraction module extracts the … This is because, the HRED model was built for general chatbots while our chatbot was more of a …

A novel semantic matching method for chatbots based on convolutional neural network and attention mechanism
F Shan, L Zhao, Y Feng – Revue d’Intelligence Artificielle, 2018 – search.proquest.com
… Then, the word2vec (W2V) algorithm was adopted for distributed representation of corpus, and the … on semantic analysis of natural language questions and the conversation between chatbot and users … Compte tenu de la popularité des Chatbots, cet article vise à développer une …

LSTM Based Self-Defending AI Chatbot Providing Anti-Phishing
SS Kovalluri, A Ashok, H Singanamala – Proceedings of the First …, 2018 – dl.acm.org
… After detecting the category, each categorized email is transferred to dedicated chatbot rooms … Each category has specially trained chatbots, and they will reply back to the spammers through the … For categorizing the emails, we have used neural network using word2vec algorithm …

Utterances classifier for chatbots’ intents
A Joigneau – 2018 – diva-portal.org
… The pre-processing is done using Word2Vec [24], a tool to train word embeddings, then many … 23], that also uses the TF-IDF algorithm, presents a more global overview on chatbots and aims … sands of tweets that result in interactions people had with the Mi- crosoft’s chatbot Tay …

A Virtual Chatbot for ITSM Application
S Raut – Asian Journal For Convergence In Technology …, 2018 – asianssr.org
… Chatbots that are developed using deep learning, mostly use a certain variant of sequence to sequence (Seq2Seq) model … 1. Chatbot module: It accepts the input from the end user in the form of natural language … Word embedding: Word2Vec is a model used for word vector …

Comparative Study of Topology and Feature Variants for Non-Task-Oriented Chatbot using Sequence to Sequence Learning
G Dzakwan, A Purwarianti – 2018 5th International Conference …, 2018 – ieeexplore.ieee.org
… Another reason is there are more OOV occurrences for word2vec (6.18%) compared to GloVe (4.22%) for Papaya … Available: https://chatbotslife.com/nlp-nlu- nlg-and-how-chatbots-work- dd7861dfc9df … [3] A. Xu, Z. Liu, Y. Guo, V. Sinha, R. Akkiraju, “A New Chatbot for Customer …

Scalable sentiment for sequence-to-sequence chatbot response with performance analysis
CW Lee, YS Wang, TY Hsu, KY Chen… – … , Speech and Signal …, 2018 – ieeexplore.ieee.org
… We pre-train the word embedding model with Word2Vec [26] and it is fixed … G(y). 3. EVALUATION METRICS Evaluation is always difficult in language generation, especially for chatbot … two metrics: sentiment coherence 1 and 2 (COH1, COH2) specially for chatbots, which give …

Memory-based matching models for multi-turn response selection in retrieval-based chatbots
X Lu, M Lan, Y Wu – CCF International Conference on Natural Language …, 2018 – Springer
… generation-based methods [1, 2, 3] and retrieval-based methods [4, 5, 6, 7]. Compared to generation-based chatbots, retrieval-based chatbots enjoy the … We train word embeddings on the training data using word2vec [15] and the dimensionality of word vectors is set as 200 …

State-of-the-Art Approaches for German Language Chat-Bot Development
N Boisgard – 2018 – ec.tuwien.ac.at
… Figure 1.2: The number of publications containing the terms “chatbot”, “chatterbot”, “chat-bot” or “chat bot … to create, host and integrate chat-bot applications, eg using Microsoft’s Bot Framework8 or IBM’s … to get an overview over the current state-of-the-art in the field of chat-bots …

Multi-turn response selection for chatbots with deep attention matching network
X Zhou, L Li, D Dong, Y Liu, Y Chen, WX Zhao… – Proceedings of the 56th …, 2018 – aclweb.org
… Building a chatbot that can naturally and con- sistently converse with human-beings on open- domain topics draws increasing research interests in past years. One important task in chatbots is response selection, which aims to select the best- matched response from a set of …

Isa: Intuit Smart Agent, A Neural-Based Agent-Assist Chatbot
Z Xue, TY Ko, N Yuchen, MKD Wu… – 2018 IEEE International …, 2018 – ieeexplore.ieee.org
… is a powerful distributed representation method introduced by Mikolov at [5]. A notable property of word2vec is that … We show that a task-specific chatbot suits our needs and propose a solution that employs … ”Chatbots and the new world of HCI.” interactions 24.4 (2017): 38-42 …

Anomaly detection for short texts: Identifying whether your chatbot should switch from goal-oriented conversation to chit-chatting
A Bakarov, V Yadrintsev, I Sochenkov – International Conference on Digital …, 2018 – Springer
… the purpose of their use: there are so-called general conversation agents, or chatbots which do … main issue comes when one wants to extend the conversational agents to a chatbot, ie to … To obtain the word embeddings we used two Word2Vec models for each language [25]: one …

Role play-based question-answering by real users for building chatbots with consistent personalities
R Higashinaka, M Mizukami, H Kawabata… – Proceedings of the 19th …, 2018 – aclweb.org
… next step is to determine if the col- lected pairs can be useful for creating chatbots that exhibit … query and the answer part of the most relevant pair is returned as a chatbot’s response … used to cal- culate the semantic similarity score between Q and Q/. We use Word2vec (Mikolov et …

First insights on a passive major depressive disorder prediction system with incorporated conversational chatbot
M Arcan, ID Wood, F Delahunty – Irish Conference on Artificial …, 2018 – library.nuigalway.ie
… Some work has already explored the possibility of building conversational chatbots that emulate a … 5 Table 1: Examples of Questions-Answer pairs used to train the conversational chatbot … ap- proach, proposed by Le and Mikolov, builds upon their existing Word2Vec al- gorithm …

EmotionPush: Emotion and Response Time Prediction Towards Human-Like Chatbots
CY Huang, LW Ku – 2018 IEEE Global Communications …, 2018 – ieeexplore.ieee.org
… 1https://code.google.com/archive/p/word2vec … This prediction has the potential to become a powerful feature that improves the user experience when interacting with chatbots … selected as Readers, as if playing the role of users in a chat scenario with the chatbot; more relevant …

Master thesis: Design and implementation of a chatbot in the context of customer support
F Peters – 2018 – matheo.uliege.be
… performing this operation, ranging from a simple count vector to deep learning approaches such as Word2vec [5] and … in “Pro- duction Ready Chatbots: Generate if not Retrieve” [18] … is the performance as- sessment and metrics used to quantify the quality of a chatbot’s behaviour …

Learning semantic similarity in a continuous space
M Deudon – Advances in Neural Information Processing Systems, 2018 – papers.nips.cc
… between pairs of sentences is an important problem in Natural Language Processing (NLP), for conversation systems (chatbots, FAQ), knowledge … done in [5] and [6]. The authors proposed unsupervised methods to learn semantic representations of words (Word2vec [5], GloVe …

Stierlitz Meets SVM: Humor Detection in Russian
A Ermilov, N Murashkina, V Goryacheva… – Conference on Artificial …, 2018 – Springer
… Rapid proliferation of conversational agents, voice interfaces, and chatbots, as well as the need to analyze large volumes of social media … of slang and sexually explicit words, polarity and subjectivity lexicons, distances between words in terms of word2vec representations, etc …

Stierlitz Meets SVM: Humor Detection in Russian
P Braslavski – Artificial Intelligence and Natural Language: 7th …, 2018 – books.google.com
… Rapid proliferation of conversational agents, voice interfaces, and chatbots, as well as the need to analyze large volumes of social media … of slang and sexually explicit words, polar- ity and subjectivity lexicons, distances between words in terms of word2vec repre- sentations, etc …

Sentimental Analysis for AIML-Based E-Health Conversational Agents
D Ireland, H Hassanzadeh, SN Tran – International Conference on Neural …, 2018 – Springer
… Sentiment analysis E-health chatbots. Download conference paper PDF … 1. Overview of the chatbot system showing the three stages … Since this corpus was derived from real chat-bot conversations, it can provide a better evaluation of the sentiment models and their estimated …

Hierarchical hybrid code networks for task-oriented dialogue
W Liang, M Yang – International Conference on Intelligent Computing, 2018 – Springer
… Unlike open-domain chatbot, task-oriented dialogue system mainly focuses on a specific task such as shopping, fault resolution, ticket booking, etc … HCNs use bag of words and average of word2vec [31] embedding to encode the utterance …

Subword Semantic Hashing for Intent Classification on Small Datasets
K Shridhar, A Sahu, A Dash, P Alonso… – arXiv preprint arXiv …, 2018 – arxiv.org
… This is the case in Intent Classification for chatbots, where typically small datasets are … for small datasets and we evaluate it on the AskUbuntu, WebApplication, and Chatbot corpora [2 … Word Embeddings are the most prominent way of embedding, thanks to Word2Vec [10] and …

What we need to learn if we want to do and not just talk
R Gangadharaiah, B Narayanaswamy… – Proceedings of the 2018 …, 2018 – aclweb.org
… 3 Proposed Approach Complete automation of customer service is still not possible as chatbots are not perfect yet … The agent or chatbot performs external actions or SQL-like queries (api call) to retrieve information … Model 6 Nearest Neighbor using Word2Vec …

Xiao-Shih: The Educational Intelligent Question Answering Bot on Chinese-Based MOOCs
HH Hsu, NF Huang – 2018 17th IEEE International Conference …, 2018 – ieeexplore.ieee.org
… Second, chatbots for casual chatting are mostly implemented by RNN (Recurrent Neural Networks) or … Thus, this kind of chatbot remain rare in educational environments especially for MOOCs … the correlations of keywords into account, the python package of “word2vec” [16] was …

EmojiGAN: learning emojis distributions with a generative model
B Mazoure, D Thang, S Ray – Proceedings of the 9th Workshop on …, 2018 – aclweb.org
… We observed that both word2vec and emoji2vec embeddings yielded only a mild amount of similarity for most emojis … This situation is reminiscent of the infamous Mi- crosoft chatbot Tay which started to pick up racist and sexist language after being trained on uncen- sored …

Disambiguating Affective Stimulus Associations for Robot Perception and Dialogue
H Siqueira, A Sutherland, P Barros… – 2018 IEEE-RAS 18th …, 2018 – ieeexplore.ieee.org
… [8], emotions have been suc- cessfully applied to the generation of responses in a chat-bot scenario … a sequence to sequence encoder-decoder architecture, the authors were able to generate coherent and emotionally relevant responses in a chatbot scenario … word2vec “song” t 3 …

Machine Learning with Swift: Artificial Intelligence for IOS
O Sosnovshchenko, O Baiev – 2018 – books.google.com
… 266 Word2Vec in Gensim 269 Vector space properties 269 iOS application 270 Chatbot anatomy 271 … Keras 296 LibSVM 296 Scikit-learn 296 XGBoost 297 NLP libraries 297 Word2Vec 297 Twitter … We’re also going to use neural networks to build several chatbots with different …

A simple end-to-end question answering model for product information
T Lai, T Bui, S Li, N Lipka – Proceedings of the First Workshop on …, 2018 – aclweb.org
… most closely related branches of work to ours are probably customer service chatbots for e … Another example is the SuperAgent (Cui et al., 2017), a powerful chatbot designed to … Using word embeddings pre-trained with word2vec (Mikolov et al., 2013) or GloVe (Pennington et al …

Enhancing Chinese Intent Classification by Dynamically Integrating Character Features into Word Embeddings with Ensemble Techniques
R Lin, C Costello, C Jankowski – arXiv preprint arXiv:1805.08914, 2018 – arxiv.org
… of multiclass user intent classification comes from the background of conversational agents, like chatbots. For example, when a chatbot system processes a user query, the first step … ??” (“walkway” and “walk”), but with embedding learning tools like Word2Vec, the commonality …

Design of an internship recruitment platform employing NLP based technologies
G Suciu, A Pasat, C B?l?ceanu, C N?drag, A Drosu – beiaro.eu
… decades of research went into the development of NLP; however, recent word2vec [5] technology … Another application is the one of Chatbots which can be integrated in several … For example, Talla [7] chatbot, searches a company’s knowledgebase for frequently asked questions …

Detecting Emotion on Indonesian Online Chat Text Using Text Sequential Labeling
RJ Hasudungan, ML Kodhra – 2018 International Symposium …, 2018 – ieeexplore.ieee.org
… For example, if the interlocutor of the chatbot is detected being sad, chatbot can show some sympathy by sending particular message in the correct time … 168 Page 3. 5. Word Embedding Word embedding made using skip-n-gram model using library word2vec …

Natural Language Processing with Java: Techniques for building machine learning and neural network models for NLP
RM Reese, AS Bhatia – 2018 – books.google.com
… the OpenNLP POSModel Summary Chapter 6: Representing Text with Features N-grams Word embedding GloVe Word2vec Dimensionality reduction … the Stanford pipeline Creating a pipeline to search text Summary Chapter 12: Creating a Chatbot Chatbot architecture Artificial …

Smart IoT and Soft AI
R Milton, D Hay, S Gray, B Buyuklieva, A Hudson-Smith – 2018 – IET
… While the chatbots used in this experiment lack the level of sophistication just described, there is an … We investi- gated the ‘gensim’ library’s implementation of the ‘word2vec’ algorithm [7], using vectors of … While this simple chatbot ‘game’ only serves as a lure for data, our analysis …

Engineering doc2vec for automatic classification of product descriptions on O2O applications
H Lee, Y Yoon – Electronic Commerce Research, 2018 – Springer
… upon receipt of the product inquiry from the online buyers, the chatbot automatically retrieves … Instead we can have chatbots respond to the requests for product registrations and inquiries … The most notable word embedding algorithm is word2vec that was devised by Mikolov et al …

Using Deep Learning and an External Knowledge Base to Develop Human-Robot Dialogues
JY Huang, TA Lin, WP Lee – 2018 IEEE International …, 2018 – ieeexplore.ieee.org
… Recently, the demand on chatbots has begun to perform open-domain conversations … It encodes the words in a sentence into numerical identifiers to form a vector representation, by using the word2vec algorithm that not only considers the mapping between the words and the …

Applications of Sequence to Sequence Models for Technical Support Automation
G Aalipour, P Kumar, S Aditham… – … Conference on Big …, 2018 – ieeexplore.ieee.org
… bgp Word2Vec [21] gateway-protocol-bgp, ospf, bgp-routing, eigrp, excluding-osis GloVe [20] ospf, eigrp, vrf … are primarily based on text matching, which is not the case in chatbots, because reasonable … Due to this lack of proper evaluation metrics for our chatbot, we had to restrict …

Mobile medical question and answer system with auto domain lexicon extraction and question auto annotation
G Yan, J Li – 2018 33rd Youth Academic Annual Conference of …, 2018 – ieeexplore.ieee.org
… In recent years, with the advent of Siri and the emergence of major manufacturers of various chatbots, QA systems have found use in … 2.We propose a method to construct a domain- specific dictionary by combining word2vec based on deep learning methods and new word …

Efficiency improvement in a busy radiology practice: determination of musculoskeletal magnetic resonance imaging protocol using deep-learning convolutional neural …
YH Lee – Journal of digital imaging, 2018 – Springer
… [9]: CNNWordEmbed(nb_labels, wvmodel = pre-trained GoogleNews Word2Vec model, nb_filters … This module could be integrated into radiologic services, such as Radiologic Chatbot, with the following functionalities; (1) a busy radiologist could confirm the pre-determined …

A semantic space approach for automatic summarization of documents
V Kaszás, MÁ Tündik, G Szaszák – 2018 9th IEEE International …, 2018 – ieeexplore.ieee.org
… can interact with humans (such as personal assistants and chatbots [8], [9 … 0.1638 Word2Vec – combined 0.2165 0.2279 0.2068 BM25 and Word2Vec 0.3319 0.2261 … A comparison between human–human online conversations and human–chatbot conversations,” Computers in …

Towards an artificially empathic conversational agent for mental health applications: System design and user perceptions
RR Morris, K Kouddous, R Kshirsagar… – Journal of medical …, 2018 – jmir.org
… commercially available products like Woebot, 7Cups, and Koko have used chatbots for various tasks … all interactions follow a simple post-response format, with the chatbot passing messages … The WMD approach uses word2vec, a word-embedding procedure that learns a vector …

Ethical challenges in data-driven dialogue systems
P Henderson, K Sinha, N Angelard-Gontier… – Proceedings of the …, 2018 – dl.acm.org
… as technical support services, and non-task-oriented dialogue systems (ie chatbots), such as … In one such case, the Microsoft Tay Chatbot was taken offline after posting messages … Many neural conversational systems use pre- trained word embeddings, such as Word2Vec [26] …

Extraction of Typical Client Requests from Bank Chat Logs
E Pronoza, A Pronoza, E Yagunova – Mexican International Conference …, 2018 – Springer
… a result of such parsing of chat logs, we obtain not only request patterns (which could be used in a chat bot system) but … Another group of methods coming from the neural networks community is represented by word embedding techniques (eg, word2vec by Google, fastText by …

Q20: Rinna riddles your mind by asking 20 questions
X Wu, H Hu, M Klyen, K Tomita, Z Chen – Japan NLP, 2018 – anlp.jp
… These 10 features include, BM25 score (Robertson and Zaragoza, 2009), word2vec distance (averaged value … a simple role-oriented mind-read- ing feature for our chatbot, Rinna (Wu … 1) improving the interestingness of real- world people’s interaction with virtual chatbots, and (2 …

Towards Automated Customer Support
M Hardalov, I Koychev, P Nakov – International Conference on Artificial …, 2018 – Springer
… However, it has been argued [10, 11] that such word-overlapping measures are not very suitable for evaluating chatbots … For all three measures, we used Google’s pre-trained word2vec embeddings because they are not learned during training, which helps … Chatbot responses …

Ximena Project
A Gaisbauer, C Tomikawa, M Zavaleta, O Blanco… – researchgate.net
… Although there are other chat- bots in the healthcare field, Ximena’s features are better equipped for the scope of our project … Vertical chatbots are closed- domain chatbots focused on particular application whereas a horizontal chatbot is a general and …

Learning how not to act in text-based games
M Haroush, T Zahavy, DJ Mankowitz, S Mannor – 2018 – openreview.net
… Our DQN architecture is tailored for text domains and uses a word2vec embedding layer followed by a simple, 2-layer … also potentially help in improving the performance of real- world, NLP systems that use DRL-like chat bots (Serban et al … A deep reinforcement learning chatbot …

Tweeting AI: Perceptions of Lay versus Expert Twitterati
L Manikonda, S Kambhampati – … International AAAI Conference on Web and …, 2018 – aaai.org
… Keyword AIT EAIT Agents Easier, Autonomous, Launched, Chatbots, Visit Explains, Strong, Worry, Safer, Struggle … Gender-based association of the AI keywords: We train the Word2Vec model on tweets about AI posted by men and women from both EAIT and AIT independently …

Enhance word representation for out-of-vocabulary on ubuntu dialogue corpus
J Dong, J Huang – arXiv preprint arXiv:1802.02614, 2018 – arxiv.org
… In this paper, we generate word embedding vectors on the training corpus based on word2vec (Mikolov et al., 2013) … Here we propose algorithm 1 to combine pre-trained word vectors with those word2vec (Mikolov et al., 2013) generated on the training set …

Customization of an example-based dialog system with user data and distributed word representations
E Seto, R Nishimura, N Kitaoka – 2018 Asia-Pacific Signal and …, 2018 – ieeexplore.ieee.org
… 37, no. 3, pp. 170–182, 2000. [5] P.-J. Chen, I.-H. Hsu, Y.-Y. Huang, and H.-Y. Lee, “Mitigating the impact of speech recognition errors on chatbot using sequence-to-sequence model,” in … 3111–3119. [10] Y. Goldberg and O. Levy, “Word2vec explained: Deriving mikolov et al.’s …

Speech Emotion Recognition Using Spectrogram & Phoneme Embedding
P Yenigalla, A Kumar, S Tripathi, C Singh… – Proc. Interspeech …, 2018 – abhayk1201.github.io
… And also phoneme embedding being trained on Word2Vec captures the semantic context too, which helps in identifying the emotion to … The proposed method can be used for similar other applications such as conversational Chatbot where identifying the emotion and sentiment …

Generating Original Jokes
T YEH, N FONG, N KERR, B COX, MH WANG – 2018 – cse.scu.edu
… This would have many benefits including chatbots having a better chance at passing the Turing test … For character based approach, we used Keras. For word based method, words are converted to feature vector with Word2Vec and RNN was trained with Ten- sorflow …

A novel approach to generate a large scale of supervised data for short text sentiment analysis
X Sun, J He – Multimedia Tools and Applications, 2018 – Springer
… Data-driven representation learning via deep learning model is effective in many field of application such as text classification, chatbot,speech recognition [35, 36], action recognition and image processing [34, 38] The crucial contributions are as … 3.1.2 Word2Vec substitution …

A Talker Ensemble: The University of Wroclaw’s Entry to the NIPS 2017 Conversational Intelligence Challenge
J Chorowski, A Lancucki, S Malik… – The NIPS’17 …, 2018 – Springer
… Word2vec algorithm was used to embed links and titles, like if they were ordinary words … Beyond these, contestants were granted free choice in defining the main purpose of their chatbots … we would like to thank everyone who was patient enough to talk to our chatbot during its …

Random Decision Syntax Trees at SemEval-2018 Task 3: LSTMs and Sentiment Scores for Irony Detection
A San – Proceedings of The 12th International Workshop on …, 2018 – aclweb.org
… In chatbots, if a chatbot misinterprets an unhappy sarcastic com- ment from a customer, the customer could become even more frustrated … We used the Google News pretrained Word2Vec (Mikolov et al., 2013) word embeddings for our model …

Avoiding echo-responses in a retrieval-based conversation system
D Fedorenko, N Smetanin, A Rodichev – Conference on Artificial …, 2018 – Springer
… embeddings of size 256, which are initialized by the pre-trained word2vec vectors [8 … match network: a new architecture for multi-turn response selection in retrieval-based chatbots … Yan, Z., et al.: DocChat: an information retrieval approach for chatbot engines using unstructured …

Classifying Eligibility Criteria in Clinical Trials Using Active Deep Learning
CH Chuan – 2018 17th IEEE International Conference on …, 2018 – ieeexplore.ieee.org
… For example, Bickmore and et al. [6] designed a chatbot for patients with low health and computer literacy to identify and learn about clinical trials … We then used the word2vec skip-gram model to learn word embeddings for the words/phrases extract from the eligibility criteria …

Auto-Encoding Dictionary Definitions into Consistent Word Embeddings
T Bosc, P Vincent – Proceedings of the 2018 Conference on Empirical …, 2018 – aclweb.org
… Page 2. 1523 and the chatbot should understand it … Dict2vec (Tissier et al., 2017) combines the word2vec skip-gram objective (predicting all the words that appear in the context of a target word) with a cost for predicting related words …

Query Understanding via Entity Attribute Identification
A Dargahi Nobari, A Askari, F Hasibi… – Proceedings of the 27th …, 2018 – dl.acm.org
… of search queries is a crucial component in virtually every semantic search system, either being a web search engine, a chatbot, or an e … the Eu- clidean distance between the vector representation of words qi and w. We obtain these vector representations form Word2Vec [13] 300 …

Memory-Based Model with Multiple Attentions for Multi-turn Response Selection
X Lu, M Lan, Y Wu – International Conference on Neural Information …, 2018 – Springer
… with the rapid growth of social conversation data on Internet, building a chatbot on open … We propose a memory-based network (MBN) for multi-turn conversation in retrieval-based chatbots … Word embeddings are pre-trained using training sets via word2vec [12] and the size is …

The Technological Gap Between Virtual Assistants and Recommendation Systems
D Rafailidis – arXiv preprint arXiv:1901.00431, 2018 – arxiv.org
… A Chatbot is a computer program that carries out a conversation through, whereas smart … Networks (ANNs), learning throughout their usage and have better performance, while Chatbots are based … For example, this will be achieved by applying the Word2Vec strategy to create …

Towards JARVIS for Software Engineering: Lessons Learned in Implementing a Natural Language Chat Interface
R Pandita, S Bucuvalas, H Bergier, A Chakarov… – Workshops at the Thirty …, 2018 – aaai.org
… Most teams starting chat-bot implementations rarely do. One alternative is to train a model on external yet similar data and then use transfer-learning to customize the model for the specific domain … word2vec. Miller, GA 1995 … A new chatbot for customer service on social media …

Can You be More Polite and Positive? Infusing Social Language into Task-Oriented Conversational Agents
YC Wang, R Wang, G Tur, H Williams – alborz-geramifard.com
… In order to have human-like and extended conversations, some researchers have studied how to incorporate social language into chatbots to generate … We conducted automatic evaluations to examine qualities of the generated text using the word2vec similarity measure [23] …

Education 4.0-Artificial Intelligence Assisted Higher Education: Early recognition System with Machine Learning to support Students’ Success
M Ciolacu, AF Tehrani, L Binder… – 2018 IEEE 24th …, 2018 – ieeexplore.ieee.org
… In this phase students are verifying their knowledge with Self-assessments questionnaires (quiz) also an intelligent Chatbot is available as … This phase means automatically correction of students exam based on course material using search Paraphrases with Word2Vec [18] and …

A Chinese Question Answering System in Medical Domain
G Feng, Z Du, X Wu – Journal of Shanghai Jiaotong University (Science), 2018 – Springer
… Furthermore, a Word2Vec model is adopted to capture the semantic meanings of words, and the questions and answers are processed with … Question answering (QA) systems are also known as chat bots, virtual assistants, which have attracted much attention in recent years [1-2 …

Introduction to Natural Language Processing and Deep Learning
P Goyal, S Pandey, K Jain – Deep Learning for Natural Language …, 2018 – Springer
… Chatbot. The most talked-about application of NLP is Chatbot. It … word . from gensim.models import Word2Vec. min_count = 0. size = 50. window = 2. sentences= “bitcoin is an innovative payment network and a new kind of money.” …

Internet v?cí pro kancelá?
M Formánek – 2018 – dspace.cvut.cz
… 8 Page 27. 1.2. Chat Bot … 1.2.1 Commerce usage Nowadays are chatbot(also called voice-assistant(“VA”) widely used in many forms … 10 Page 29. 1.3. Speech to Text “bis später”. There are many methods how to solve this ranking problem, for example TF-IDF, Word2Vec etc …

Assigning Personality/Profile to a Chatting Machine for Coherent Conversation Generation.
Q Qian, M Huang, H Zhao, J Xu, X Zhu – IJCAI, 2018 – ijcai.org
… are pre-trained on an unlabeled corpus (about 60, 000, 000 Weibo posts) with word2vec … from speaker-tagged di- alogue data, our work allows system developers to control chatbots’ profile explicitly … Our work moves toward endowing a chatbot with control- lable personality …

Measuring Depression Symptom Severity from Spoken Language and 3D Facial Expressions
A Haque, M Guo, AS Miner, L Fei-Fei – arXiv preprint arXiv:1811.08592, 2018 – arxiv.org
… Additionally, people experience psychological benefits from disclosing emotional experiences to chatbots [17] … Psychological, relational, and emotional effects of self-disclosure after conversations with a chatbot … Linguistic: Word2Vec embeddings [29] …

Drift in Online Social Media
A Mullick, A Bhandari, A Niranjan… – 2018 IEEE 9th …, 2018 – ieeexplore.ieee.org
… its various characteristics in online social media as the foundation of developing automatic chat moderator or multi-functional chat bot that can (i … Based on these features and comment-comment sim- ilarity using word2vec model, we identify: (i) whether the comment of “Reply-To …

Neural Response Ranking for Social Conversation: A Data-Efficient Approach
I Shalyminov, O Dušek, O Lemon – arXiv preprint arXiv:1811.00967, 2018 – arxiv.org
… made it possi- ble to collect large numbers of dialogues between real users of Amazon Echo devices and various chatbots … (2015, 2016) use a heuristic based on keyword match- ing, part-of-speech filters, and Word2Vec similar- ity … 2017. A deep reinforcement learning chatbot …

Improving Multilingual Semantic Textual Similarity with Shared Sentence Encoder for Low-resource Languages
X Tang, S Chen, L Do, Z Min, F Ji, H Yu… – arXiv preprint arXiv …, 2018 – arxiv.org
… The com- mon approach is to take advantage of pretrained word em- beddings such as Word2Vec (Mikolov et al … The data set was constructed based on online chatlog of a QA chat- bot. If the answer of chatbot is correct, the user query and the knowledge title of the answer is …

The First Conversational Intelligence Challenge
M Burtsev, V Logacheva, V Malykh, IV Serban… – The NIPS’17 …, 2018 – Springer
… Using word2vec, the system embeds a large dataset of utterances with their contexts, and retrieves best matching utterance pairs from the associated … Meanwhile, the quality of chatbots can also be defined by user success in the task, in a way that a good chatbot should be …

A Framework for domain-specific natural language information brokerage
L Ni, J Liu – Journal of Systems Science and Systems Engineering, 2018 – Springer
… The rest of the paper is organized as follows: Section 2 presents related works on chatbots and question … The patient interacts with M andy through a mobile chatbot … The word embedding algorithm we apply is Google’s Word2Vec that maps words into their semantic vector …

Automatic conditional generation of personalized social media short texts
Z Wang, J Wang, H Gu, F Su, B Zhuang – Pacific Rim International …, 2018 – Springer
… Nevertheless, language generation with personalities is demanding in some important application cases, including intelligent customer service and chat bots … 2. Every input Chinese word is embedded into k dimensional representation vector by word2vec [14] …

“I think it might help if we multiply, and not add”: Detecting Indirectness in Conversation
P Goel, Y Matsuyama, M Madaio, J Cassell – articulab.hcii.cs.cmu.edu
… For example, the Twitter-like nature of collaborative educational conversations can be exploited like we did using a word2vec model pre-trained on tweets … Reynolds, M.: Chatbots learn how to drive a hard bargain (2017) 38 …

Out-of-domain detection method based on sentence distance for dialogue systems
KJ Oh, DK Lee, C Park, YS Jeong… – … Conference on Big …, 2018 – ieeexplore.ieee.org
… improves the accuracy of the out-of-domain detection(OOD) method, and we apply this method to develop a chatbot system for … Word2Vec is one of the well- known vector-space representation models, and it enables semantic or syntactic similarity between words and sentences …

Beyond” How may I help you?”: Assisting Customer Service Agents with Proactive Responses
M Wan, X Chen – arXiv preprint arXiv:1811.10686, 2018 – arxiv.org
… the response candidates, and regard the ultimate response suggestion task as a candidate ranking problem; 2) different from the chatbot system (Cui … start with all tokenized sen- tences from agents’ messages in our live-chat conversa- tion data and apply word2vec (Mikolov et al …

ShareBox: Designing A Physical System to Support Resource Exchange in Local Communities
MV Law, M Naaman, N Dell – Proceedings of the 2018 on Designing …, 2018 – dl.acm.org
… The conversational chatbot is implemented us- ing Microsoft’s bot framework [49], with message parsing through Microsoft’s Language Understanding Intelligent Ser … Item queries are further filtered through an off-the-shelf imple- mentation of word2vec [25, 26, 51, 60] trained on …

Neural response generation with dynamic vocabularies
Y Wu, W Wu, D Yang, C Xu, Z Li – Thirty-Second AAAI Conference on …, 2018 – aaai.org
… We study response generation for open domain conversation in chatbots … Introduction Together with the rapid growth of social conversation data on Internet, there has been a surge of interest on build- ing chatbots for open domain conversation with data driven approaches …

Improving Mild Cognitive Impairment Prediction via Reinforcement Learning and Dialogue Simulation
F Tang, K Lin, I Uchendu, HH Dodge, J Zhou – arXiv preprint arXiv …, 2018 – arxiv.org
… In the context of Alzheimer’s disease research, [29] designed a virtual reality based chat-bot to evaluate memory loss using predefined questions and answers. [34] discussed applica- tions of chat-bots as caregiviers for Alzheimer’s patients, providing safety, personal assistance …

Analysis, discovery and exploitation of open data for the creation of question-answering systems
G Molina Gallego – 2018 – rua.ua.es
… French phrase [Kyunghyun Cho, 2014], also system for automatic summarization or Word2Vec models using … Chatbots have been become more popular from the last two decades, actually, many companies … To better understand the potential of a chatbot, it is needed to know …

Resolving Abstract Anaphora Implicitly in Conversational Assistants using a Hierarchically stacked RNN
P Khurana, P Agarwal, G Shroff, L Vig – Proceedings of the 24th ACM …, 2018 – dl.acm.org
… We first learn word em- beddings ?(?) using word2vec model [19] on all the queries, answers, and the related policy documents together … Using this network we predict the word embedding of correctly spelled words, as learned by using word2vec [19] …

PacGAN: The power of two samples in generative adversarial networks
AK Khetan – 2018 – ideals.illinois.edu
… processing (eg frame prediction [8], image super-resolution [9], and image-to-image transla- tion [10]), as well as dialogue systems or chatbots—applications where one may need realistic … in the area of natural language processing (eg word2vec [11]). GANs have the potential to …

Did You Just Assume My Vector? Detecting Gender Stereotypes in Word Embeddings
A Bakarov – researchgate.net
… weighted vectors from the sample of gender-neutral set with category c; the amount of such samples equals k. Evaluation of Word2Vec models trained on different corpora … of word embeddings is crucial if they are implemented in public services like chatbots or search engines …

Why You Should Listen to This Song: Reason Generation for Explainable Recommendation
G Zhao, H Fu, R Song, T Sakai, X Xie… – 2018 IEEE International …, 2018 – ieeexplore.ieee.org
… of reason generation for explainable rec- ommendation in conversation applications, we assume that a user U has asked the chatbot to recommend a … Specifically, we first project the user tag into a pre- trained Word2Vec model3 [41] and discover similar words in terms of cosine …

Sentient Embodied Conversational Agents: Architecture and Evaluation
D TELLOLS, M LOPEZ-SANCHEZ… – … , New Trends and …, 2018 – books.google.com
… However, the aforementioned chatbots have limitations when embedded in appli- cations requiring more complex conversations and human-like properties–in … we will obtain a word embedding for each sentence to facilitate the following analysis steps using Word2Vec model by …

Advanced Social Interaction with Agents: 8th International Workshop on Spoken Dialog Systems
M Eskenazi, L Devillers, J Mariani – 2018 – Springer
… domain systems is a challenge, while multi-domain is almost a prerequisite for open-domain chatbots … These systems can be characterized as combining more than one slot-filling or chatbot system … Their use of this information in a word2vec set-up further increased accuracy …

Measuring semantic coherence of a conversation
S Vakulenko, M de Rijke, M Cochez… – International Semantic …, 2018 – Springer
… Distribution of cosine distances for different data splits using Word2Vec and GloVe word embeddings (left), and RDF2Vec KG embeddings (top right … 1. Athreya, RG, Ngonga, A., Usbeck, R.: Enhancing community interactions with data-driven chatbots – the DBpedia chatbot …

Content-aware tweet location inference using quadtree spatial partitioning and jaccard-cosine word embedding
O Ajao, D Bhowmik, S Zargari – 2018 IEEE/ACM International …, 2018 – ieeexplore.ieee.org
… Calculation of linear vector: Linear vector calculations are implemented on feature vectors using word2vec. An example of this is King – Man + Woman = Queen … However, it should be noted that chat bots may not always generate duplicate messages …

Towards effective AI-powered agile project management
HK Dam, T Tran, J Grundy, A Ghose… – arXiv preprint arXiv …, 2018 – arxiv.org
… contrast, latest advances in deep learning-based NLP techniques [4] such as word2vec, paragraph2vec, Long … The chatbot can be asked different types of questions, such as “Show me your estimate … Future chatbots can be trained end-to-end [14] and person- specific instead of …

Domain Knowledge Driven Key Term Extraction for IT Services
P Mohapatra, Y Deng, A Gupta, G Dasgupta… – … Conference on Service …, 2018 – Springer
… a knowledge graph, which provides context information and inference capabilities for search and chat-bots … which affects the quality of cognitive applications on top of search, chat-bot/dialog systems … word2vec is applied after annotating common terms of upto three words as a …

Human Conversation Analysis Using Attentive Multimodal Networks with Hierarchical Encoder-Decoder
Y Gu, X Li, K Huang, S Fu, K Yang, S Chen… – 2018 ACM Multimedia …, 2018 – dl.acm.org
… timent analysis and speaker trait detection, is useful in many real- world applications such as medical support, activity recognition, chatbots, etc … Figure 2): Text: To capture textual word-level representations, we first embed each word using a pretrained word2vec dictionary [16] …

Tailored Sequence to Sequence Models to Different Conversation Scenarios
H Zhang, Y Lan, J Guo, J Xu, X Cheng – … of the 56th Annual Meeting of …, 2018 – aclweb.org
… in many natural language processing applications such as customer services, intelligent assistant and chat- bot … the experiments on the pub- lic Chinese Weibo dataset (social chatbot) show that … For Ubuntu, we use word embeddings trained by word2vec on the training dataset …

On the dimensionality of word embedding
Z Yin, Y Shen – Advances in Neural Information Processing Systems, 2018 – papers.nips.cc
… This is possibly due to the influence of the groundbreaking paper, which introduced the skip-gram Word2Vec model and chose a dimensionality of 300 [Mikolov et al., 2013a] … Figure 2: skip-gram Word2Vec: over-parametrization does not significantly hurt performance …

Sentiment classification with word localization based on weakly supervised learning with a convolutional neural network
G Lee, J Jeong, S Seo, CY Kim, P Kang – Knowledge-Based Systems, 2018 – Elsevier
… In the proposed model, words are embedded in a fixed-size of continuous vector space using Word2Vec [32], GloVe [33], and FastText [34] … CAM 2 -Multichannel uses the word vectors pre-trained by the Word2Vec, GloVe, and FastText …

Supervised Transfer Learning for Product Information Question Answering
T Lai, T Bui, N Lipka, S Li – 2018 17th IEEE International …, 2018 – ieeexplore.ieee.org
… corpus on which to learn the initial word embeddings, such as word2vec [17] or … C. Customer Service Chatbots Developing customer service chatbots for ecommerce web- sites is an … SuperAgent introduced in [19] is a powerful chatbot designed to improve online shopping experi …

NEXUS Network: Connecting the Preceding and the Following in Dialogue Generation
H Su, X Shen, W Li, D Klakow – arXiv preprint arXiv:1810.00671, 2018 – arxiv.org
… online conver- sational data, there has been a surge of in- terest in building open-domain chatbots with data … The word vector di- mension is 300 and is initialized with the pub- lic Word2Vec (Mikolov et al., 2013 … RL: Deep reinforcement learning chatbot as in (Li et al., 2016c) …

Response selection of multi-turn conversation with deep neural networks
Y Wang, Z Yan, Z Li, W Chao – CCF International Conference on Natural …, 2018 – Springer
… And main parameters of word2vec are set as follows: size is 200, window is 8, sample is 1e-5, cbow is 0, min_count is 6. Parameters not mentioned are … Wu, Y., et al.: Sequential matching network: a new architecture for multi-turn response selection in retrieval-based chatbots …

NEXUS Network: Connecting the Preceding and the Following in Dialogue Generation
X Shen, H Su, W Li, D Klakow – Proceedings of the 2018 Conference on …, 2018 – aclweb.org
… online conver- sational data, there has been a surge of in- terest in building open-domain chatbots with data … The word vector di- mension is 300 and is initialized with the pub- lic Word2Vec (Mikolov et al., 2013 … RL: Deep reinforcement learning chatbot as in (Li et al., 2016c) …

Dave the debater: a retrieval-based and generative argumentative dialogue agent
DT Le, CT Nguyen, KA Nguyen – Proceedings of the 5th Workshop on …, 2018 – aclweb.org
… 3.1 Format of a debate The aim of the chatbot is to be able to carry a conversation with humans to debate about a given topic … Page 4. 124 ture of the sentences. For the embedding layer, we use the pre-trained word2vec of Google News dataset3(Mikolov et al., 2013a) …

Bangla Interrogative Sentence Identification from Transliterated Bangla Sentences
MM Hamid, T Alam, S Ismail… – … Conference on Bangla …, 2018 – ieeexplore.ieee.org
… for the development of smart assist applications, medical applications, question-answering based applications, user-interactive applications, chatbot pro- grams … By forming Convolutional Neural Network of one layer of Convolution with the help of word2vec and static vectors, it …

A Review on Artificial Intelligence Decision Making Support System
SS Harnish Shah – j-asc.com
… Moreover, QA can be used to develop dialogue systems and chatbots. Therefore … sentences. For evaluation, word embeddings were used to calculate cosine distance and divergence of two sentences using Word2Vec model …

Addressing the Soft Impacts of Weak AI-Technologies
K Gabriels – Artificial Life Conference Proceedings, 2018 – MIT Press
… The Word2vec algorithm, which was used to find patterns in word embeddings in Google News articles, disclosed sexism: ‘man is to computer programmer as … shape the data that algorithms have to learn from and this can go wrong, as the case of Microsoft’s AI chatbot Tay also …

Unfolding Recurrent Neural Networks
P Goyal, S Pandey, K Jain – Deep Learning for Natural Language …, 2018 – Springer
… The word2vec models aim to initialize random vectors for each word, which are further learned to have meaningful vectors, to perform specific … Sequence-to-sequence (seq2seq) models are used for everything from chatbots to speech-to-text to dialog systems to QnA to image …

A Question Type Driven Framework to Diversify Visual Question Generation.
Z Fan, Z Wei, P Li, Y Lan, X Huang – IJCAI, 2018 – ijcai.org
… of ar- eas, eg, providing demonstrations in child education [Ku- nichika et al., 2004], initializing a conversation for chat- bots [Mostafazadeh et al … Embedding vectors are initialized by the word embeddings (from word2vec) of their correspond- ing interrogative words and would be …

Deep Neural Language Generation with Emotional Intelligence and External Feedback
V Srinivasan – 2018 – search.proquest.com
… We train our own word2vec embeddings with appended valence, arousal and dominance [3] scores as … Next, the chatbot uses that information to come up with a relevant answer that is … As the chatbots become emotionally in tune, people could have more fun chatting with them …

Emotional dialogue generation using image-grounded language models
B Huber, D McDuff, C Brockett, M Galley… – Proceedings of the 2018 …, 2018 – dl.acm.org
… Table 3: Results of automatic linguistic analysis (a scalable complement to the human ratings.) The relative improvement in the dialogue BLEU and word2vec scores are shown as per- centages (compared to the text-only model) … The word2vec score for the text and image …

Natural Language Processing with TensorFlow: Teach language to machines using Python’s deep learning library
T Ganegedara – 2018 – books.google.com
… 255 Word2vec to the rescue 255 Generating text with Word2vec 256 Examples generated with LSTM-Word2vec and beam … for source and target sentences 361 Other applications of Seq2Seq models – chatbots 363 Training a chatbot 364 Evaluating chatbots – Turing test …

Alquist 2.0: Alexa Prize Socialbot Based on Sub-Dialogue Models
J Pichl, CTU FEE, P Marek, J Konrád, M Matulík… – dex-microsites-prod.s3.amazonaws …
… Moreover, we compared the impact of using word2vec and fastText embeddings for each architecture … We use task six because it is the only task which contains records of real-world conversations between humans and chatbot …

Chat More If You Like: Dynamic Cue Words Planning to Flow Longer Conversations
L Yao, R Xu, C Li, D Zhao, R Yan – arXiv preprint arXiv:1811.07631, 2018 – arxiv.org
… The simulation process between two chatbots (sharing same parameters) consists of following steps: 1) An initial instance (Qi,j, Fi,j) from training data is fed to agent A as input … To speed up training, we pre-trained Word2Vec (Mikolov et al …

Inter-Category Distribution Enhanced Feature Extraction for Efficient Text Classification
Y Wang, J Huang, Y Liu, L Tu, L Liu – International Conference on Big …, 2018 – Springer
… algorithms have been applied successfully in many big data driven text applications and services, such as spam filtering [2], tagging online news [3], social media analysis [4], bioscience [5] and chat bot [6]. Statistical … Zhu et al. [17] proposed a method using word2vec model to …

Predicting Human Trustfulness from Facebook Language
M Zamani, A Buffone, HA Schwartz – arXiv preprint arXiv:1808.05668, 2018 – arxiv.org
… Table 3 demonstrates the predictive perfor- mance of our model in comparison to the senti- ment and word2vec baselines … Thus, the present model may be helpful for the generation of trustful chat bots, such as virtual as- sistants or therapeutic aids. References …

Design of an Intelligent Agent for Stimulating Brainstorming
CH Wang, TY Li – Proceedings of the 2018 10th International …, 2018 – dl.acm.org
… 2. RELATED WORKS In previous years, chatbots established on instant messaging software or web-based Q&A systems have attracted much … documents from the online encyclopedia, Wikipedia, as the training data for the neural networks in the Word2Vec algorithm [10] …

From Emoji Usage to Categorical Emoji Prediction
G Guibon, M Ochs, P Bellot – … and Intelligent Text …, 2018 – hal-amu.archives-ouvertes.fr
… To embed tweets with their emojis we used two approaches using Word2Vec [18,14] in its gensim implementation11 … can be used to recommend the emotion cat- egories to express by an embodied conversational agent or in general dialog system, such as trending chatbots …

The Effect of Data Quantity on Dialog System Input Classification Models
J Lipecki, V Lundén – 2018 – diva-portal.org
… were surprisingly similar for classification purposes; the popular Word2vec n-gram word … systems without domain constraints. Also, both sources reserve the term chatbot for the … demand for knowledge”. Adding to this, the 2018 State of Chatbots Report [8] find that “by …

Multitask learning for neural generative question answering
Y Huang, T Zhong – Machine Vision and Applications, 2018 – Springer
… Building chatbot in human–computer conversation via natural language is one of the most … the topic information into the encoder–decoder framework to generate interesting responses for chatbots … In the above models, the word embeddings are initialized by Word2Vec 4 [22 …

An empirical study on fine-grained named entity recognition
K Mai, TH Pham, MT Nguyen, NT Duc… – Proceedings of the 27th …, 2018 – aclweb.org
… Moreover, for subsequent applications such as search engines or chatbot platforms to easily utilize the FG-NER results, we want to classify an entity … Consequently, we use the embeddings based on GloVe for English5. For Japanese, we use pretrained word2vec6 embeddings …

Dialog manager for conversational AI
BP Marek – 2018 – core.ac.uk
… 4 2.2.1 Word2vec … 59 Page 17. Chapter 1 Introduction Personal voice assistants and text chatbots are newly emerging types of user interface. Their increasing popularity drives the need for better dialogue managers. This need will be accel …

Dialogový manažer pro konverza?ní um?lou inteligenci
P Marek – 2018 – dspace.cvut.cz
… 4 2.2.1 Word2vec … 59 Page 17. Chapter 1 Introduction Personal voice assistants and text chatbots are newly emerging types of user interface. Their increasing popularity drives the need for better dialogue managers. This need will be accel …

Intent Detection System Based on Word Embeddings
K Balodis, D Deksne – International Conference on Artificial Intelligence …, 2018 – Springer
… There are several tools for generating word embeddings such as gloVe [18], word2vec [15], fastText [2] and … we use the Wit.ai service 1 which is one of few popular chatbot creation services … Shawar, BA, Atwell, E.: Machine learning from dialogue corpora to generate chatbots …

A 20% Jump in Duplicate Question Detection Accuracy? Replicating IBM team’s experiment and finding problems in its data preparation
J Silva, J Rodrigues, V Maraev, C Saedi, A Branco – META, 2018 – lrec-conf.org
… Both tasks have been useful to support conversational interfaces and chat- bots, in general, and online question & answering (Q&A) community forums, in … for all the other parameters, which are not described in the DSEQ paper, were taken from the word2vec vanilla parameters …

Emotion Detection and Classification in a Multigenre Corpus with Joint Multi-Task Deep Learning
S Tafreshi, M Diab – Proceedings of the 27th International Conference on …, 2018 – aclweb.org
… 6 We experimented with google news (trained using word2vec), wikipedia+Gigaword (trained using GloVe), Twitter (trained using GloVe).7 The best results … Emotion detection has attracted several NLP applications like chatbots, stock market, and human person- ality analysis …

Semi-automatic sentiment analysis based on topic modeling
T Sokhin, N Butakov – Procedia Computer Science, 2018 – Elsevier
… There are many practical applications, which require to extract sentiment from texts: advertising analytics, interactive chat bots, opinion mining … According to this, we think that quality may be estimated by word2vec [7] representation of topics …

Retrieval-Enhanced Adversarial Training for Neural Response Generation
Q Zhu, L Cui, W Zhang, F Wei, Y Chen, T Liu – arXiv preprint arXiv …, 2018 – arxiv.org
… They have been widely used in real-world applications, including customer service systems, personal assistants, and chatbots … The word embeddings are pre- trained on the training set using the Word2Vec toolkit4. The dimensionality of the embeddings is set to 500 …

Inferring User Emotive State Changes in Realistic Human-Computer Conversational Dialogs
R Li, Z Wu, J Jia, J Li, W Chen, H Meng – 2018 ACM Multimedia …, 2018 – dl.acm.org
… chenweibj8871@sogou-inc.com Helen Meng The Chinese University of Hong Kong hmmeng@se.cuhk.edu.hk ABSTRACT Human-computer conversational interactions are increasingly per- vasive in real-world applications, such as chatbots and virtual assis- tants …

CCG supertagging via Bidirectional LSTM-CRF neural architecture
R Kadari, Y Zhang, W Zhang, T Liu – Neurocomputing, 2018 – Elsevier
… To obtain the fixed word embedding of each word we use a pretrained word embeddings model. Our best model use pre-trained Google’s Word2Vec 300-dimensional embeddings trained on 100 billion words from Google News [32] … Word embedding, Word2vec …

Virtual assistant with natural language processing capabilities
C Mas – 2018 – upcommons.upc.edu
… 12 1. Chatbots ….. 12 1.1 … 12 1.2. Type of Chatbot … 17 2.3.3. Similarity measures based on Word2vec …

Response Selection and Automatic Message-Response Expansion in Retrieval-Based QA Systems using Semantic Dependency Pair Model
MH Su, CH Wu, KY Huang, WH Lin – ACM Transactions on Asian and …, 2018 – dl.acm.org
… It is because of the wide range of plausible responses and the lack of phrase alignment between the post and the response [8]. The retrieval-based chatbots choose a response from the … A QA system that serves as a chatbot for emotional support and comforting is thus desirable …

Response Generation For An Open-Ended Conversational Agent
N Dziri – 2018 – era.library.ualberta.ca
… 25 2.4.1 Chatbot systems … lowing this path of investigation so as to mimic human behavior in generating fluent and engaging responses. Nowadays, chatbots are gaining popularity worldwide and big companies are increasingly investing millions of dollars to 1 Page 15 …

Forming of Dyadic Conversation Dataset for Bahasa Indonesia
C Tho, AS Setiawan, A Chowanda – Procedia Computer Science, 2018 – Elsevier
… First, each word of the question sentence h will be converted into a vector using word2vec un- til … This format was used since generally, chatbot systems use JSON or XML format … as Embodied Conversation Agent (ECA)21,22, or Chat Bot22, where the ECA or Chat Bot would be …

Semantic Matching Using Deep Multi-Perception Semantic Matching Model with Stacking
X Cao, X Liu, B Zhu, Q Miao, C Hu, F Xu – ceur-ws.org
… It is of great importance for various NLP tasks such as automatic question answering, chat bot, information retrieval, and machine trans- lation … Existing semantic models, such as Word2Vec, LDA, etc., can determine the similarity between text …

Python: Beginner’s Guide to Artificial Intelligence: Build applications to intelligently interact with the world around you using Python
D Rothman, M Lamons, R Kumar, A Nagaraja, A Ziai… – 2018 – books.google.com
… up the model Adding services to a chatbot A cognitive chatbot service The … Summary Chapter 14: Improve the Emotional Intelligence Deficiencies of Chatbots Technical requirements … RNN Step 3 – producing data augmentation Word embedding The Word2vec model Principal …

Natural Language Processing and Computational Linguistics: A practical guide to text analysis with Python, Gensim, spaCy, and Keras
B Srinivasa-Desikan – 2018 – books.google.com
… This technique is generally referred to as word embeddings, and Word2Vec and Doc2Vec are two … a lot of the concepts we have explored throughout the book are sentiment analysis and chatbots … In this chapter, we will not be providing the code to build a chatbot or sentiment …

Tweet Sentiment Visualization and Classification Using Manifold Dimensionality Reduction
F GRIMALDO, E LÓPEZ-IÑESTA… – … , New Trends and …, 2018 – books.google.com
… been succesfully applied in Customer Management Relationship services to deal with user suggestions and complaints in social networks or chatbots [7, 5 … the Paragraph Vector with Distributed Mem- ory model (PV-DM)[16], which is an extension the the word2vec algorithm [20 …

Learn what not to learn: Action elimination with deep reinforcement learning
T Zahavy, M Haroush, N Merlis… – Advances in Neural …, 2018 – papers.nips.cc
… al., 2016b; Liu et al., 2017; Zhao and Eskenazi, 2016; Wu et al., 2016), travel planners (Peng et al., 2017), restaurant/hotel bookers (Budzianowski et al., 2017), chat-bots (Serban et … On smaller data sets, using word2vec (Mikolov et al., 2013) yields good performance (Kim, 2014 …

Creating an Emotion Responsive Dialogue System
A Vadehra – 2018 – uwspace.uwaterloo.ca
… Customer support or food ordering chatbots are examples of task spe- cific conversational agents where the success of the system is determined … are various shallow neural network models that are used to compute the embed- ding space like GloVe [60], Word2Vec [51], fastText …

A Bi-Encoder LSTM Model for Learning Unstructured Dialogs
D Shekhar – 2018 – digitalcommons.du.edu
… Abstract Creating a data-driven model that is trained on a large dataset of unstructured dialogs is a crucial step in developing a Retrieval-based Chatbot systems. This thesis presents a Long … 35 2.3 Current State of Research on Chatbot Systems …

Infogain-Driven Dialogue Modeling with Hashcode Representations
S Garg, I Rish, G Cecchi, S Ghazarian… – arXiv preprint arXiv …, 2018 – researchgate.net
… Therapy chatbots, such as Woebot [Fitzpatrick et al., 2017] and similar systems, are becoming increasingly popular; however, these agents have limited ability to understand free text and have to resort to a fixed set of prepro … 10https://code.google.com/archive/p/word2vec/ Page 6 …

Towards Interpretable Chit-chat: Open Domain Dialogue Generation with Dialogue Acts
W Wu, C Xu, Y Wu, Z Li – 2018 – openreview.net
… Open domain dialogue generation has been widely applied to chatbots which aim at engaging users by keeping conversation going … Data in Baidu Tieba covers a large variety of topics, and thus can be viewed as a simulation of open domain conversation in a chatbot …

Comparing the Effectiveness of Support Vector Machines and Convolutional Neural Networks for Determining User Intent in Conversational Agents
KO Sullivan – 2018 – arrow.dit.ie
… 1.1 Background Conversational agents are computer systems which communicate with users employing natural language and fall into two broad categories; chatbots and task-oriented agents (Jurafsky & Martin, 2009). Chatbots are systems which attempt to converse with …

Sémantická podobnost v?t pro úlohu rozpoznání úmyslu
T Brich – 2018 – dspace.cvut.cz
… Other thanks belong to the members of the Alquist chat bot team, who kindly provided me with their implementation of an intent recognition system and a dataset to compare it with my results … 3 2 Embedding algorithms …..4 2.1 Word2Vec …..4 2.2 FastText …

Semantic Sentence Similarity for Intent Recognition Task
T Brich – 2018 – core.ac.uk
… Other thanks belong to the members of the Alquist chat bot team, who kindly provided me with their implementation of an intent recognition system and a dataset to compare it with my results … 3 2 Embedding algorithms …..4 2.1 Word2Vec …..4 2.2 FastText …

Intent Generation for Goal-Oriented Dialogue Systems based on Schema. org Annotations
U ?im?ek, D Fensel – arXiv preprint arXiv:1807.01292, 2018 – arxiv.org
… In Proceedings of First International Workshop on Chatbot in conjunction with ICWSM 2018 … Unlike more conversation oriented, human-human interaction mim- icking chatbots, goal-oriented … based on existing ConceptNet 5.5 knowledge graph3 data, word2vec embeddings [11 …

Ruber: An unsupervised method for automatic evaluation of open-domain dialog systems
C Tao, L Mou, D Zhao, R Yan – Thirty-Second AAAI Conference on Artificial …, 2018 – aaai.org
… 2015)—may also fit the query, but it does not make much sense in a commercial chatbot.1 The observation implies that a groundtruth alone is insufficient for the evaluation of … In the referenced metric, we trained 50- dimensional word2vec embeddings on the Douban dataset …

Neural networks for sentiment analysis in AsterixDB
JMK Finckenhagen – 2018 – brage.bibsys.no
… Using the offset between words in the vectorspace, the Word2Vec model is able to discover more than just syntactic similarities, and it has been shown that performing simple … Self-driving cars, intelligent personal assistants like Siri and Alexa and chatbots are all over the news …

Chinese pinyin aided IME, input what you have not keystroked yet
Y Huang, H Zhao – arXiv preprint arXiv:1809.00329, 2018 – arxiv.org
… Word embeddings are pre-trained by word2vec (Mikolov et al., 2013) toolkit on the adopted cor- pus and … Lsequential matching network: A new architecture for multi-turn response selection in retrieval-based chatbots … Lingke: A fine-grained multi-turn chatbot for customer service …

Concorde: Morphological Agreement in Conversational Models
D Polykovskiy, D Soloviev… – Asian Conference on …, 2018 – proceedings.mlr.press
… Neural conversational models are widely used in applications such as personal assistants and chat bots … in a wide range of applications, from simple rule-based chatbots to complex … (2016) use bidirectional RNNs, initialize the weights with word2vec representations trained on …

Evaluation of real-time deep learning turn-taking models for multiple dialogue scenarios
D Lala, K Inoue, T Kawahara – Proceedings of the 2018 on International …, 2018 – dl.acm.org
… is also influential for turn-taking [21] and the requirements of a suitable turn-taking system will differ between a question-answering system and a conversational chatbot … Word embedding was conducted using Word2Vec [15] on the tokenizations with a dimension of 100 …

Review of State-of-the-Art in Deep Learning Artificial Intelligence
VV Shakirov, KP Solovyeva… – Optical Memory and …, 2018 – Springer
… While Go programs present successful examples of pairing modern RL with modern CNN, RL can be combined with neural chat bots and rea- soners [63, 64] … It’s like an unsupervised objective func- tion somewhat similar to what is used for example in word2vec …

Contextual Advertising Engine
GAA Rodrigues – 2018 – estudogeral.sib.uc.pt
… Table 19: Intention Detection Experiment 1: GloVe results…..99 Table 20: Intention Detection Experiment 1: Word2vec results…..100 … The surface of it is being scratched by Customer Support Chat Bots, but there is still …

Double embeddings and cnn-based sequence labeling for aspect extraction
H Xu, B Liu, L Shu, PS Yu – arXiv preprint arXiv:1805.04601, 2018 – arxiv.org
… This is especially important when the model is deployed in a real-life application (eg, chatbot), where a complex model will slow down the speed of infer- ence. Thus, to achieve competitive performance whereas keeping the model as simple as possible is important …

Automating Incident Classification Using Sentiment Analysis and Machine Learning
MD Ibrishimova, KF Li – … on Intelligent, Secure, and Dependable Systems …, 2018 – Springer
… We are confident in the overall accuracy of sentiment analysis because recent advances in machine learning and in particular word embedding algorithms such as word2vec have greatly … We designed an interactive incident response chatbot to gather the incident report …

Understand functionality and dimensionality of vector embeddings: the distributional hypothesis, the pairwise inner product loss and its bias-variance trade-off
Z Yin – arXiv preprint arXiv:1803.00502, 2018 – arxiv.org
… Some popular embedding procedures include the Latent Semantic Analysis (LSA) (Deerwester, Dumais, Furnas, Landauer, and Harshman, 1990), GloVe (Pennington, Socher, and Manning, 2014) and skip-gram Word2Vec (Mikolov, Chen, Corrado, and Dean, 2013a) …

Efficient Purely Convolutional Text Encoding
S Malik, A Lancucki, J Chorowski – arXiv preprint arXiv:1808.01160, 2018 – arxiv.org
… Such approaches have been applied by participants of recent chat- bot contests: The 2017 Alexa Prize … Kiros et al., 2015] generalizes idea of unsu- pervised learning of word2vec word embeddings … using a method similar to the one used in Poetwannabe chatbot [Chorowski et al …

Improving Dialog Systems Using Knowledge Graph Embeddings
B Carignan – 2018 – curve.carleton.ca
… variety of tasks. Some of the more widely used word embedding methods include Word2Vec [3] and GloVe [4]. These methods use large unstructured corpora, such as … 6 2.1.2 Early Chatbots ELIZA [11] is an early chatbot program which uses a series of scripts to process user …

Building Sequential Inference Models for End-to-End Response Selection
JC Gu, ZH Ling, YP Ruan, Q Liu – arXiv preprint arXiv:1812.00686, 2018 – arxiv.org
… be roughly divided into two categories : (1) task-oriented systems and (2) non-task- oriented systems (also known as chatbots) … embeddings (Pen- nington, Socher, and Manning 2014) and 100-dimensional embeddings estimated on the training set using Word2Vec (Mikolov et …

Exploring convolutional neural networks and topic models for user profiling from drug reviews
E Tutubalina, S Nikolenko – Multimedia Tools and Applications, 2018 – Springer
… of models: topic models with user attributes such as PLDA and USTM, and neural models based on CNNs on top of word2vec embeddings … Chat bots can actively talk to patients in order to collect relevant information, but an even better idea might be to use passive solutions that …

Adversarial learning for chinese NER from crowd annotations
YS Yang, M Zhang, W Chen, W Zhang, H Wang… – Thirty-Second AAAI …, 2018 – aaai.org
… We require the crowd annotators to label the types of entities, including person, song, brand, product, and so on. Identifying these entities is useful for chatbot and e-commerce platforms (Klüwer 2011) … In Dialog domain (DL), we collect raw sentences from a chatbot application …

Deep Learning with Applications Using Python
NK Manaswi, NK Manaswi, S John – 2018 – Springer
… 146 Designs and Functions of Chatbots …..146 Steps for Building a Chatbot …..147 Preprocessing Text and Messages …..148 …

Deep Learning for Natural Language Processing
P Goyal, S Pandey, K Jain – 2018 – Springer
… Negative Sampling …..91 Word2vec Code …..92 … 171 Why Are Chatbots Such a Big Opportunity … Building a Chatbot Can Sound Intimidating …

Hierarchical variational memory network for dialogue generation
H Chen, Z Ren, J Tang, YE Zhao, D Yin – … of the 2018 World Wide Web …, 2018 – dl.acm.org
… We use the publicly available Word2Vec4 to train word embed- ding … 3We release the corpus at https://github.com/chenhongshen/HVMN. 4https://code.google.com/archive/p/word2vec/ 5We use version 5 in our work. 6https://github.com/SUTDNLP/ZPar …

Frustrated, Polite, or Formal: Quantifying Feelings and Tone in Email
N Chhaya, K Chawla, T Goyal, P Chanda… – Proceedings of the …, 2018 – aclweb.org
… The closest work in frustration detection is re- lated to interactions and conversations with intel- ligent chatbots (Wang et al., 2004; D’Mello et al … We train a Word2Vec CBOW model (Mikolov et al., 2013) on raw 517,400 emails from the EN- RON email dataset to obtain the word …

Response ranking with deep matching networks and external knowledge in information-seeking conversation systems
L Yang, M Qiu, C Qu, J Guo, Y Zhang… – The 41st International …, 2018 – dl.acm.org
Page 1. Response Ranking with Deep Matching Networks and External Knowledge in Information-seeking Conversation Systems Liu Yang1 Minghui Qiu2 Chen Qu 1 Jiafeng Guo3 Yongfeng Zhang4 W. Bruce Croft1 Jun Huang2 Haiqing Chen2 …

The RLLChatbot: a solution to the ConvAI challenge
N Gontier, K Sinha, P Henderson, I Serban… – arXiv preprint arXiv …, 2018 – arxiv.org
… Furthermore, since Alexa is a voice-activated assistant, the chatbot relies on the accuracy of the speech recognizer provided. Many chatbots have been proposed for this challenge, overall they all rely on modern deep learning and reinforcement learning techniques and try to …

A Computational Social Science Framework for Learning and Visualizing the Latent Language of Structured IoT Interaction Data
T Novak, DL Hoffman – Available at SSRN 3278045, 2018 – papers.ssrn.com
… development efforts. Keywords: assemblage theory, discovery, Internet of Things, topological data analysis, word2vec Page 3 … Currently, more than 20 billion smart objects, such as smart home devices, chatbots, social robots, sensors, and the services that …

KNADIA: Enterprise KNowledge Assisted DIAlogue Systems Using Deep Learning
M Singh, P Agarwal, A Chaudhary… – 2018 IEEE 34th …, 2018 – ieeexplore.ieee.org
… However, in view of the high expectations from such a system, it becomes especially challenging: Users might not be particularly perturbed if, for example Google Assistant gives an incorrect answer; however, if an HR chatbot gives misleading guidance, the organization might …

Hands-On Natural Language Processing with Python: A practical guide to applying deep learning architectures to your NLP applications
R Arumugam, R Shanmugamani – 2018 – books.google.com
… Using Shallow Models Word vectors 70 70 The classical approach Word2vec 71 72 … Summary Chapter The Question-Answering 9: Question-Answering task and Chatbots Using Memory … Dialog datasets The bAbI dialog dataset Raw data format Writing a chatbot in TensorFlow …

Snips voice platform: an embedded spoken language understanding system for private-by-design voice interfaces
A Coucke, A Saade, A Ball, T Bluche, A Caulier… – arXiv preprint arXiv …, 2018 – arxiv.org
Page 1. Snips Voice Platform: an embedded Spoken Language Understanding system for private-by-design voice interfaces Alice Coucke Alaa Saade Adrien Ball Théodore Bluche Alexandre Caulier David Leroy Clément Doumouro Thibault Gisselbrecht Francesco Caltagirone …

Benchmarking authorship attribution techniques using over a thousand books by fifty Victorian era novelists
A Gungor – 2018 – scholarworks.iupui.edu
… University Challenge organized by Roche. We have created a data driven and visu- ally stunning chatbot. Thank you team, for your hard work and making our time at Purdue worthwhile. Page 5. v PREFACE … 48 4.10 Word2Vec 2-D Closest Words for ‘listen’ …

Neural Creative Language Generation
M Ghazvininejad – 2018 – search.proquest.com
… business data (Anand and Kahn, 1992). The widespread use of the Internet intro- duced new NLG applications. Generating canned responses, customer service chat … Page 16. bots, and conversation agents like Siri and Cortana are a few examples. Mean …

Natural Language Semantic Construction Based on Cloud Database
S Wang, L Zhang, Y Zhang, J Sun… – CMC-COMPUTERS …, 2018 – tsp.techscience.com
… Page 6. 608 Copyright © 2018 Tech Science Press CMC, vol.57, no.3, pp.603-619, 2018 (2) Using Word2vec to train the words, which are similar to the keywords of the document will be extracted. a) Using Word2vec to train the divided words into bin files …

Polite dialogue generation without parallel data
T Niu, M Bansal – Transactions of the Association of Computational …, 2018 – MIT Press
… Most current chatbots and conversational mod- els lack any such style, which can be a social issue because human users might learn biased styles from such interactions, eg, kids learning to be rude be- cause the dialogue system encourages short, curt re- sponses, and also …

PROJECT ON VIDEO SHOT BOUNDARY DETECTION
SC MANDAL – 2018 – rcciit.org
Page 1. PROJECT ON VIDEO SHOT BOUNDARY DETECTION REPORT OF MAJOR PROJECT SUBMITTED OF PARTIAL FULFILLMENT FOR THE DEGREE OF MASTER OF COMPUTER APPLICATION SANTOSH CHANDRA MANDAL …

A Neural Generation-based Conversation Model Using Fine-grained Emotion-guide Attention
Z Zhou, M Lan, Y Wu – 2018 International Joint Conference on …, 2018 – ieeexplore.ieee.org
… 4https://github.com/pytorch/pytorch 5https://code.google.com/archive/p/word2vec … [2] Y. Wu, W. Wu, C. Xing, C. Xu, Z. Li, and M. Zhou, “A sequential matching framework for multi-turn response selection in retrieval-based chatbots,” in ACL, 2017 …

PICA: Proactive Intelligent Conversational Agent for Interactive Narratives
J Falk, S Poulakos, M Kapadia… – … of the 18th …, 2018 – disneyresearch.s3.amazonaws.com
… Conversational Agents: Eliza [38] and ALICE [14] are both chat- bots using rules and pattern matching … By searching for an intersection between their synonym groups using WordNet [13] and utilizing Word2Vec [23] to retrieve a similarity … A Deep Reinforcement Learning Chatbot …

Moon IME: neural-based chinese pinyin aided input method with customizable association
Y Huang, Z Li, Z Zhang, H Zhao – Proceedings of ACL 2018, System …, 2018 – aclweb.org
… The pre-trained pinyin embed- dings and Chinese word embeddings are trained by word2vec (Mikolov et al., 2013) toolkit on Wikipedia4 and unseen words are … 2017. Sequential matching network: A new architecture for multi-turn response selection in retrieval-based chatbots …

Deep Learning for Digital Text Analytics: Sentiment Analysis
M Kale, P Mankame, G Kulkarni – arXiv preprint arXiv:1804.03673, 2018 – arxiv.org
… ments [5], catchphrase extraction for legal phrase extraction [5], paraphrase detec- tion, sentiment analysis, question-answering – chat bots, document summarization … to the representational advantage over other methods [5]. As this model is an extension of word2vec with the …

Priority Based Sentiment Analysis for Quick Response to Citizen Complaints
KV Deshmukh, SS Shiravale – 2018 3rd International …, 2018 – ieeexplore.ieee.org
… Elsevier 2016 [6] Zhang, D., Xu, H., Su, Z., & Xu, Y. “Chinese comments sentiment classification based on word2vec and svm … 1–6 ,2013 [25] S reshmi and Kannan Balakrishnan, “Implementation of an inquisitive chatbot for database supported knowledge bases” Springer, vol 41 …

Emotion Detection in Text: a Review
A Seyeditabari, N Tabari, W Zadrozny – arXiv preprint arXiv:1806.00674, 2018 – arxiv.org
… One can also argue it is necessary to create better artificial intelligence tools, eg chatbots … Some of the more well-established and most frequently used em- bedding models in the literature are latent semantic analysis or LSA, Word2Vec (Mikolov et al., 2013a; Mikolov et al …

Finding Good Representations of Emotions for Text Classification
JH Park – arXiv preprint arXiv:1808.07235, 2018 – arxiv.org
… ous vector representations like word2vec have become the new norm for NLP problems … When training NLP models, such as chatbots, things do not always go as intended. Famous incident of Microsoft chatbot Tay, which learned directly from users’ tweets with …

OurDirection: An Interactive Dialogue Framework For Chatting with Government Officials
S Abrishamkar, JX Huang – Proceedings of the ACM Symposium on …, 2018 – dl.acm.org
… The word embedding space, such as Word2Vec [8] and GloVe [9] approximate the meaning of the word by calculating the co- occurrence of the words in the corpus … 2016. DocChat: An Information Retrieval Approach for Chatbot Engines Using Unstructured Documents. In ACL.

Unsupervised Dialogue Act Classification with Optimum-Path Forest
LCF Ribeiro, JP Papa – 2018 31st SIBGRAPI Conference on …, 2018 – ieeexplore.ieee.org
… The DA classification task can also be seen as a sub-problem for other tasks, such as the development of chatbots where the … B. Feature extraction Word vector models, such as Glove [39], word2vec [40] and fastText [41], have become the cornerstone of modern NLP approaches …

Exemplar encoder-decoder for neural conversation generation
G Pandey, D Contractor, V Kumar, S Joshi – Proceedings of the 56th …, 2018 – aclweb.org
… As the test outputs for HRED are not available for Technical Support dataset, we use our 4GoogleNews-vectors-negative300.bin from https:// code.google.com/archive/p/word2vec/ 5https://github.com/julianser/ hed-dlg-truncated/blob/master/ Evaluation/embedding_metrics …

Quality Assessment of Conversational Agents: Assessing the Robustness of Conversational Agents to Errors and Lexical Variability
J Guichard – 2018 – diva-portal.org
… services, serve as virtual assistants, or take part in social conversations. In recent years, these agents, also known as chatbots, have become more and more popular. Many companies see them as a cost effective and viable …

SOC: hunting the underground inside story of the ethereum Social-network Opinion and Comment
TTHD Huang, PW Hong, YT Lee, YL Wang… – arXiv preprint arXiv …, 2018 – arxiv.org
… presented a LSTM and CNN-based deep neural network model, which utilizes word2vec and linguistic embeddings for claim classification … goal is to optimize the amount of parameters, net- work structure, and release automated detection tools, public RESTful API and chatbot …

Sentiment Analysis on Financial News and Microblogs
C Talekar – 2018 – search.proquest.com
… Some of the NLP tasks are speech recognition, summarization, word sense disambiguation, question answering using chatbots, named entity recognition, sentiment analysis etc … aspect-specific and targeted, Word2vec (shallow neural network) based, and deep learning based …

Natural Language Processing and Attentional-Based Fusion Strategies for Multimodal Sentiment Analysis
J Chen – 2018 – imperial.ac.uk
… Another popular use of sentiment analysis can be found in automatic dialogue sys- tems, such as ChatBot … Where each word has a 1D vector representation as word embeddings that could be learned from word2vec[30], gloVe[31] or FastText[32] …

SOGO: A Social Intelligent Negotiation Dialogue System
R Zhao, OJ Romero, A Rudnicky – Proceedings of the 18th International …, 2018 – dl.acm.org
… User: okay I guess. Agent: Playing with you is making me a smarter chatbot … fastText is essentially an extension of the word2vec model, which treats each word as a composition of character n-grams. We have set n as in the range between 3 and 6 (default value) …

DeepSumm: a deep learning approach to text summarization
R CAMPO – 2018 – politesi.polimi.it
… From everyday use applications like Google Translate and chatbots like Siri, Cortana and Alexa, to more challenging tasks like YouTube automatic … more and more attention from non-IT industry too, as, for example, many company websites now feature a chatbot for customer …

Dialogue generation: From imitation learning to inverse reinforcement learning
Z Li, J Kiseleva, M de Rijke – arXiv preprint arXiv:1812.03509, 2018 – arxiv.org
… a dialogue generation system: the first employs defined rules or templates to construct possible responses and the second builds a chatbot to learn … For all three metrics, we use pre-trained Word2Vec word embeddings trained on the Google News Corpus, which is public access …

A Method for Dataset Creation for Dialogue State Classification in Voice Control Systems for the Internet of Things
I Shilin, L Kovriguina, D Mouromtsev… – … Readings in Language …, 2018 – ceur-ws.org
… The model was trained on the raw text without preprocessing using the word2vec library [Mikolov et al., 2013], using the skip- gram algorithm and a vector size of 100 … [Jurafsky and Martin, 2017] Jurafsky, D., and Martin, JH (2017) Dialogue Systems and Chatbots // Speech and …

Explicit Interaction Model towards Text Classification
C Du, Z Chin, F Feng, L Zhu, T Gan, L Nie – arXiv preprint arXiv …, 2018 – arxiv.org
… subsections. Interaction Layer Interaction mechanism is widely used in tasks of matching source and target textual contents, such as natural language inference (Wang and Jiang 2016b) and retrieve-based chat- bot (Wu et al. 2017) …

Personalized response generation by Dual-learning based domain adaptation
M Yang, W Tu, Q Qu, Z Zhao, X Chen, J Zhu – Neural Networks, 2018 – Elsevier
… 1. Introduction. Conversational system (also called dialogue system) has become increasingly important in a large variety of applications, such as e-commerce, technical support services, entertaining chatbots, information retrieval dialogue systems …

Hacia un diccionario global
E Iklódi – 2018 – riunet.upv.es
… An early version of conversational agents and certain strongly domain-based chatbots are already out on the market, providing 24 hour, immediate assistance for customers … It briefly presents the standard word2vec learning procedure for monolingual word vectors and …

Role of data properties on sentiment analysis of texts via convolutions
E Çano, M Morisio – World Conference on Information Systems and …, 2018 – Springer
… becoming a hype in computing industry. Self-driving cars, intelligent personal assistants and chat bots passing Turing test, are some examples of today’s deep learning revolution. In particular, Convolution Neural Networks (CNNs …

Topic-based evaluation for conversational bots
F Guo, A Metallinou, C Khatri, A Raju… – arXiv preprint arXiv …, 2018 – arxiv.org
… The word embedding matrix can be initialized with any pre-trained embeddings such as GloVe [18] and Word2Vec [15, 16], while the topic-word attention matrix is … From Table 7, we can see that the RER correlates well negatively with the user ratings for 15 chatbots (? = -0.717) …

Attentive Semantic Role Labeling with Boundary Indicator
Z Zhang, S He, Z Li, H Zhao – arXiv preprint arXiv:1809.02796, 2018 – arxiv.org
… For Chinese, we exploit Wikipedia documents to train the same dimensional Word2Vec embeddings (Mikolov et al., 2013) … Pengfei Zhu, Zhuosheng Zhang, Jiangtong Li, Yafang Huang, and Hai Zhao. 2018. Lingke: A fine-grained multi-turn chatbot for customer service …

Data Augmentation for Neural Online Chat Response Selection
W Du, AW Black – arXiv preprint arXiv:1809.00428, 2018 – arxiv.org
… 5.2 Training We initialize word embeddings using the results of word2vec (Mikolov et al., 2013) trained on the whole corpus … 2016. Sequential matching network: A new architecture for multi-turn response selec- tion in retrieval-based chatbots. arXiv preprint arXiv:1612.01627 …

How copyright law can fix artificial intelligence’s implicit bias problem
A Levendowski – Wash. L. Rev., 2018 – HeinOnline
… In 2013, Google announced the release of word2vec, a toolkit capable of representing how words are used in relation to one another so as to better understand their meanings.’ Word2vec can recognize that Beijing is to China in the same way as Warsaw is to Poland, as capital …

Efficient Large-Scale Stance Detection in Tweets
Y Yan, J Chen, ML Shyu – International Journal of Multimedia Data …, 2018 – igi-global.com
… Afterthat,theauthoruseddescriptivestatisticsmethodsandconcludedthatTrump’s campaignknewmoreabouthowtouseTwitterchatbots … in ourmodelistheembeddinglayer,which mapsvocabularywordindicesintolow-dimensionalvector representations,ie,word2vecvectors …

Text Summarization using Natural Language Processing
Z Luo – 2018 – cs.wpi.edu
… related articles. Juniper Networks is looking for ways to be able to automatically summarize these articles so that chatbot can present the summaries to the customers. The customers can then … The similarity score was calculated using Google’s Word2Vec public model …

Improving Response Selection in Multi-turn Dialogue Systems
D Chaudhuri, A Kristiadi, J Lehmann… – arXiv preprint arXiv …, 2018 – arxiv.org
Page 1. arXiv:1809.03194v1 [cs.AI] 10 Sep 2018 Improving Response Selection in Multi-turn Dialogue Systems by Incorporating Domain Knowledge Debanjan Chaudhuri Smart Data Analytics Group University of Bonn & Fraunhofer IAIS Germany chaudhur@cs.uni-bonn.de …

Measuring Short Text Semantic Similarity with Deep Learning Models
J Ge – 2018 – yorkspace.library.yorku.ca
… In [61], Mikolov et al. propose an algorithm called word2vec, in which two architectures to word2vec are developed … tributes to the eventual popularization of word embeddings through the creation of word2vec, a toolkit enabling the training and use of pre-trained embeddings 22 …

Other Applications
A Vieira, B Ribeiro – Introduction to Deep Learning Business Applications …, 2018 – Springer
… Asgari et al. [AM15] adopted the skip-gram model (used on Word2vec) and showed that it could effectively learn a distributed representation of biological sequences with general … Despite all the buzz around chatbots, they definitely will change the way users interact with content …

Deep Context Resolution
J Chen – 2018 – uwspace.uwaterloo.ca
… iii Page 4. Abstract Conversations depend on information from the context. To go beyond one-round con- versation, a chatbot must resolve contextual information such as: 1) co-reference resolution, 2) ellipsis resolution, and 3) conjunctive relationship resolution …

Data-Driven Input Feature Augmentation for Named Entity Recognition
??? – 2018 – s-space.snu.ac.kr
… 44 5.1 Word2Vec Model Parameters … A variation of the named entity recognition task is also used in the spoken language understanding (SLU) component of dialog management systems, or ”chatbots”, along with the intent detection classification task. In the common …

Towards Explainable and Controllable Open Domain Dialogue Generation with Dialogue Acts
C Xu, W Wu, Y Wu – arXiv preprint arXiv:1807.07255, 2018 – arxiv.org
… conversation. 1 Introduction Recently, there is a surge of interest on dialogue generation for chatbots which aim to naturally and meaningfully converse with humans on open do- main topics (Vinyals and Le, 2015). Although …

Polisis: Automated analysis and presentation of privacy policies using deep learning
H Harkous, K Fawaz, R Lebret, F Schaub… – 27th {USENIX} Security …, 2018 – usenix.org
… a visual overview of the different aspects of each privacy policy, a chatbot for answering … While general-purpose pre-trained embeddings, such as Word2vec [24] and GloVe [25] do … policy and the users, especially in conver- sational interfaces (eg, voice assistants and chatbots) …

Synonym Expansion for Large Shopping Taxonomies
A Boteanu, A Kiezun, S Artzi – 2018 – openreview.net
… with product search. For the experiments in this section, we used a set of unigram and bigram embedding vectors generated by applying the word2vec algorithm on the search query dataset [Mikolov et al., 2013]. We used the …

Response selection from unstructured documents for human-computer conversation systems
Z Yan, N Duan, J Bao, P Chen, M Zhou, Z Li – Knowledge-Based Systems, 2018 – Elsevier
… We conduct comprehensive experiments on both real human-machine conversation scenarios and sentence selection benchmarks. Side-by-side evaluation between DocChat and a famous chatbot demonstrates that DocChat performs better on domain related queries …

Applied Natural Language Processing with Python
T Beysolow II – Springer
… Word2Vec …..90 … Some examples of implementations using deep learning are chatbots that handle customer service requests, auto-spellcheck … For example, if someone spoke to a chatbot and asked it to “find food near …

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