Vector Space & Chatbots 2020


Notes:

Vector space model (or term vector model) is an algebraic model for representing text documents (and any objects, in general) as vectors of identifiers, such as, for example, index terms.

Resources:

Wikipedia:

References:

See also:

100 Best Support Vector Machine VideosSVM (Support Vector Machine) & Chatbots 2018


Lifelong knowledge learning in rule-based dialogue systems
B Liu, C Mei – arXiv preprint arXiv:2011.09811, 2020 – arxiv.org
… We believe that to advance the practical chatbot technology, one key direction is to make chatbots learn from users online … Our work in this paper represents a major step towards building a learning chatbot … Iris: a chatoriented dialogue system based on the vector space model …

Developing Dialog Manager in Chatbots via Hybrid Deep Learning Architectures
B Ali, V Ravi – Intelligent Data Engineering and Analytics, 2020 – Springer
… All these Chatbots, independent of the domain, have a common behavior, ie, task oriented which … three hybrid deep learning architectures for the dialog manager to be used in Chatbot … K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space (2013) …

Improving Access to Justice with Legal Chatbots
M Queudot, É Charton, MJ Meurs – Stats, 2020 – mdpi.com
… dialog system chatbot; information retrieval; natural language processing; question answering system; dialog system … In practice, we develop Information Retrieval (IR)-based chatbots in two different … First, we introduce in Section 2 recent developments in chatbot technology in …

Conversational Word Embedding for Retrieval-Based Dialog System
W Ma, Y Cui, T Liu, D Wang, S Wang, G Hu – arXiv preprint arXiv …, 2020 – arxiv.org
… future, we will adapt the method to more neural models especially the generation- based methods for the dialog system … TripleNet: Triple attention network for multi- turn response selection in retrieval-based chatbots … Efficient estimation of word representations in vector space …

An Application-Independent Approach to Building Task-Oriented Chatbots with Interactive Continual Learning
S Mazumder, B Liu, S Wang… – … the Loop Dialogue Systems, 2020 – cs.uic.edu
… Task-oriented chatbots like virtual assistants are essentially built as Natural Language (command) Interfaces … it can form the core of an application independent task-oriented dialogue system as it … the scoring function of Matcher M. (3) CML-vsm: Tf-idf based vector space model is …

Intelligent Chatbot for Lab Security and Automation
VA Prasad, R Ranjith – 2020 11th International Conference on …, 2020 – ieeexplore.ieee.org
… Vector quantization (VQ) maps the vectors inside the space from a broad vector space to a finite number … The proposed system in this paper is a rule-based voice-based structured chatbot that is developed … [2] Darius Zumstein and Sophie Hundertmark, “Chatbots – An Interactive …

Implementation of Artificial Intelligence Based Chatbot System With Long Term Memory
M Gupta, P Bhilare, S Katkade, U Kerkar… – Available at SSRN …, 2020 – papers.ssrn.com
… Many researchers have explored the use of deep learning recurrent neural network architecture to develop efficient chatbots.[8] … Each word is represented as real valued vectors ,of hundreds of dimensions ,in a predefined vector space … [1]. “Chatbot: Artificially Intelligent …

Implementation of Artificial Intelligence Based Chatbot System with Long Term Memory
S Katkade, U Kerkar, P Bhilare, M Gupta, P Thakur – 2020 – easychair.org
… Many researchers have explored the use of deep learning recurrent neural network architecture to develop efficient chatbots.[8] … Each word is represented as real valued vectors ,of hundreds of dimensions ,in a predefined vector space … [1]. “Chatbot: Artificially Intelligent …

Survey on evaluation methods for dialogue systems
J Deriu, A Rodrigo, A Otegi, G Echegoyen… – Artificial Intelligence …, 2020 – Springer
In this paper, we survey the methods and concepts developed for the evaluation of dialogue systems. Evaluation, in and of itself, is a crucial part during.

A framework for building closed-domain chat dialogue systems
M Nakano, K Komatani – Knowledge-Based Systems, 2020 – Elsevier
… Closed-domain chatbot. Dialogue system development framework. Non-task-oriented dialogue system … Section 2 mentions previous work related to closed-domain chatbots … It won first prize at the dialogue system live competition held in Nov., 2018 [9]. The system built by …

On Dialogue Systems Based on Deep Learning
Y Fan, X Luo, P Lin – International Journal of Computer and …, 2020 – publications.waset.org
… Multi-turn chatbot based on query-context attentions and dual wasserstein generative adversarial networks … Efficient estimation of word representations in vector space … Sequential matching network: A new architecture for multi-turn response selection in retrieval-based chatbots …

A Hybrid Model to Classify Sudden Topic Change, Misunderstanding and Non-understanding in Human Chat-bot Interaction
M Tewari, M Jingar, S Bensch – 2020 – diva-portal.org
… Physics and Technology (YI) and Workshop and Session Series on on Chatbots and Conversational … where Amazon Mechanical Turk (AMT) workers were assigned to have conversations with YI chatbot … H.: Iris: A chat-oriented dialogue system based on the vector space …

Study on emotion recognition and companion Chatbot using deep neural network
MC Lee, SY Chiang, SC Yeh, TF Wen – MULTIMEDIA TOOLS AND …, 2020 – Springer
… In the past, chat bots can only handle simple information … To achieve intelligent medical practice, the Chatbot is further expected to be applied to the services, including … model in 2013 [32], followed by several scholars [33–37], has replaced the traditional vector space model as …

A deep learning based chatbot for cultural heritage
G Sperlí – Proceedings of the 35th Annual ACM Symposium on …, 2020 – dl.acm.org
… name entity and on other hand to project the input question in the same vector space of the … 2018. Content- oriented user modeling for personalized response ranking in chatbots … A Survey on Chatbot Implementation in Customer Service Industry through Deep Neural Networks …

Natural language understanding in argumentative dialogue systems
PR Shigehalli – 2020 – oparu.uni-ulm.de
… In addition to VPAs, DS also find extensive applications in chatbots … Hence the chat bot responses would become unreliable for a strategic user arguments like challenging previous … For the proposed dialog system design, it is necessary to use a word embedding which contains …

An overview of machine learning in chatbots
P Suta, X Lan, B Wu, P Mongkolnam… – Int J Mech Engineer …, 2020 – ijmerr.com
… The common techniques for vector representation are: • word2vec [29]: Each word is represented by a vector in a specified vector space containing continuous bag-of-word (CBOW) and skip … The current trend in chatbot development suggests that chatbots will continue …

Role-Aware Enhanced Matching Network for Multi-turn Response Selection in Customer Service Chatbots
G Zhao, Y Zhu, S Feng, D Wang, Y Zhang… – … Conference on Advanced …, 2020 – Springer
… Context and response must be projected properly into the vector space to capture the relationship between … et al.: AliMe Chat: a sequence to sequence and rerank based chatbot engine … et al.: Multi-hop selector network for multi-turn response selection in retrieval-based chatbots …

The Margarita Dialogue Corpus: A Data Set for Time-Offset Interactions and Unstructured Dialogue Systems
A Chierici, N Habash, M Bicec – … of The 12th Language Resources and …, 2020 – aclweb.org
… A dialogue system like a TOIA formulates a new category of chatbots that can … The distance gives us a ranking function for every answer in the KB: the closer the question relative to a given answer in the KB for an interrogator’s question in the sentence vector space, the higher …

A Survey of Dialogue System Evaluation
Y Fan, X Luo – 2020 IEEE 32nd International Conference on …, 2020 – ieeexplore.ieee.org
… 2) open-domain dialogue systems (also be called chat systems or a chatbot) [1], which … CIDEr [40] Combination of BLEU and vector space model to calculate the cosine similarity between … systems: In the response quality evaluation of a task-based dialogue system, according to …

Cleveree: an artificially intelligent web service for Jacob voice chatbot
A Wicaksana – Telkomnika, 2020 – search.proquest.com
… 468-472, 2019. [4] S. Wijaya and A. Wicaksana, “Jacob Voice Chatbot Application Using Wit … [6] VA Bhagwat, “Deep Learning for Chatbots,” MS Thesis, Sch … 111-142, 2016. [20] T. Mikolov, et al., “Efficient Estimation of Word Representations in Vector Space,” ICLR: Proceeding of …

Chatbot: A Conversational Agent employed with Named Entity Recognition Model using Artificial Neural Network
N Ali – arXiv preprint arXiv:2007.04248, 2020 – arxiv.org
… There are several tools available online to build Chatbots without complex coding … [6] YW Chandraa and S. Suyantoa, “Indonesian Chatbot of University … Recursive neural networks can learn logical semantics,” in Proceedings of the 3rd Workshop on Continuous Vector Space …

Length Adaptive Regularization for Retrieval-based Chatbot Models
D Wang, H Fang – Proceedings of the 2020 ACM SIGIR on International …, 2020 – dl.acm.org
… Unfortunately, none of the state of the art retrieval-based chat- bot models including SMN[22 … over- favor longer responses, which limits the retrieval performance of the chatbots especially for … favoring long documents and improves the retrieval performance for the chatbot models …

Hierarchical Interactive Matching Network for Multi-turn Response Selection in Retrieval-Based Chatbots
T Yang, R He, L Wang, X Zhao, J Dang – International Conference on …, 2020 – Springer
… Christopher, F., WohlwendJeremy, Tao, L.: Building a production model for retrieval-based chatbots … dialogue corpus: a large dataset for research in unstructured multi-turn dialogue systems … G., Dean, J.: Efficient estimation of word representations in vector space (2013)Google …

An Adaptive Response Matching Network for Ranking Multi-turn Chatbot Responses
D Wang, H Fang – International Conference on Applications of Natural …, 2020 – Springer
… T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space … Qiu, M., et al.: AliMe chat: a sequence to sequence and rerank based chatbot engine … M.: A sequential matching framework for multi-turn response selection in retrieval-based chatbots …

Benchmarking Intent Detection for Task-Oriented Dialog Systems
H Qi, L Pan, A Sood, A Shah, L Kunc… – arXiv preprint arXiv …, 2020 – arxiv.org
… The ATIS and SNIPS datasets have been created with focus on voice interactive chatbots … These tokenized training utterances are concatenated and transformed to TF/IDF vector space … but trains much faster – which is a key factor in usability of a commercial chatbot solution …

Investigation of Sentiment Controllable Chatbot
H Lee, CH Ho, CF Lin, CC Chang, CW Lee… – arXiv preprint arXiv …, 2020 – arxiv.org
… In contrast to goal-oriented dialogue systems [1], [2], chat- bot chats with human users on any … It is usually emotionless, which is a major limitation of modern chatbots as emotion plays a … social interaction, especially in chatting [6]. Hence we seek to train the chatbot to generate …

Response generation to out-of-database questions for example-based dialogue systems
S Isonishi, K Inoue, D Lala, K Takanashi… – … Dialogue Systems for …, 2020 – Springer
… response) from a database using methods such as keyword matching or vector space modeling, and the … pp 212–215Google Scholar. 3. Kawahara T (2018) Spoken dialogue system for a … network: a new architecture for multi-turn response selection in retrieval-based chatbots …

Natural language processing In chatbot development: how does a chatbot process language?
A Heikkilä – 2020 – jyx.jyu.fi
… BOT PROCESS LANGUAGE … is not deemed mature enough yet, there has also a demand found for emotional support and companionship using chatbots (Zamora, 2017 … in this thesis lies in the gap between question answering system as well as a functional chatbot, de- pending …

Improving Out-of-Scope Detection in Intent Classification by Using Embeddings of the Word Graph Space of the Classes
P Cavalin, VHA Ribeiro, A Appel… – Proceedings of the 2020 …, 2020 – aclweb.org
… (2018) is employed for mapping the classes into a vector space, although we … a public dataset described in (Larson et al., 2019) called here the Larson dataset2; a real dataset from a finance chatbot; and a pool of 40 datasets in two different languages from chatbots built using …

Demonstration of Hospital Receptionist Robot with Extended Hybrid Code Network to Select Responses and Gestures
EJ Hwang, BK Ahn, BA Macdonald… – 2020 IEEE International …, 2020 – ieeexplore.ieee.org
… [Accessed: 11-Sep-2018]. [2] Z. Yan et al., “DocChat: An Information Retrieval Approach for Chatbot Engines Using Unstructured … 516–525, doi: 10.18653/v1/p16-1049. [3] RE Banchs and H. Li, “IRIS: a Chat-oriented Dialogue System based on the Vector Space Model,” in …

Understanding patient complaint characteristics using contextual clinical BERT embeddings
B Saha, S Lisboa, S Ghosh – arXiv preprint arXiv:2002.05902, 2020 – arxiv.org
… 2 shows how the related text is represented closer in vector space … Available: http://dx.doi.org/ 10.18653/v1/W19-5034 [3] S. Ghosh, S. Bhatia, and A. Bhatia, “Quro: Facilitating user symptom check using a personalised chatbot-oriented dialogue system,” Stud Health …

A Chatbot For Interacting with SDMX Databases
G Thiry, I Manolescu, L Liberti – lix.polytechnique.fr
… The general framework for this kind of chatbots is to use the user’s inputs to fill a set of frames (origin city, destination city … RDF3 format and the development of its as- sociated with query language, ie SPARQL4. Several projects have aimed at implementing chatbot systems over …

Towards Similar User Utterance Augmentation for Out-of-Domain Detection
A Azpeitia, M Serras, L García-Sardiña… – … Dialogue Systems for …, 2020 – Springer
… use of Dialogue Systems (DS)—more commonly known as Voice Assistants or chatbots—is increasing … varied, many of them might not be very relevant for the target chatbot scenario, since … 2014) Soft similarity and soft cosine measure: similarity of features in vector space model …

DisBot: a portuguese disaster support dynamic knowledge chatbot
J Boné, JC Ferreira, R Ribeiro, G Cadete – Applied Sciences, 2020 – mdpi.com
… From 2015 on, chatbot research showed an exponential growth, displaying a progress from virtually no publications in the year 2000, to thousands of publications in 2019. Personal assistants and social chatbots have been, by far, the main focus of this field’s applications in the …

MateBot: The Design of a Human-Like, Context-Sensitive Virtual Bot for Harmonious Human-Computer Interaction
Z Wang, B Guo, H Wang, H Cui, Y He, Z Yu – International Conference on …, 2020 – Springer
… The earliest chatbot Eliza Weizenbaum [22], proposed in 1966, was used to imitate a … Therefore, chatbots can only imitate human dialogue behaviors and do not respond to the … two different latent codes through \({F_s}\) and \({F_{cs}}\) to express features in vector space …

End-to-end response selection based on multi-level context response matching
BEA Boussaha, N Hernandez, C Jacquin… – Computer Speech & …, 2020 – Elsevier
… Retrieval systems. chatbots. neural networks. goal-oriented dialogue systems. DSTC … they have proved their efficiency in both academia and industry such as the Alibaba’s chatbot AliMe (Qiu … In this paper, we describe our end-to-end single-turn multi-level dialog system which we …

Coach: A Coarse-to-Fine Approach for Cross-domain Slot Filling
Z Liu, GI Winata, P Xu, P Fung – arXiv preprint arXiv:2004.11727, 2020 – arxiv.org
… related slot types in certain domains for user utterances, and are an indispensable part of task-oriented dialog systems … map the representation of the slot entity belonging to the same slot type into a similar vector space … Xpersona: Eval- uating multilingual personalized chatbot …

Continuous and Interactive Factual Knowledge Learning in Verification Dialogues
S Mazumder, B Liu, N Ma, S Wang… – … -2020 Workshop on …, 2020 – openreview.net
… Chatbots often use KBs to answer user questions … This paper focuses on another opportunity, ie, when the user asks the chatbot a factual verification (yes/no) question that the chatbot cannot answer … Our Predictor is based on the compositional vector space model [36, 13] …

Clustering Approach to Topic Modeling in Users Dialogue
E Feldina, O Makhnytkina – Proceedings of SAI Intelligent Systems …, 2020 – Springer
… User dialogue texts collected during a chatbot competition from real users [7] or independently as … Fasttext is a method of displaying words in a vector space using neural networks so … T., Rudnicky, A.: RubyStar: A Non-Task-Oriented Mixture Model Dialog System (2017)Google …

OWI: Open-World Intent Identification Framework for Dialog Based System
J Parmar, S Soni, SS Chouhan – International Conference on Big Data …, 2020 – Springer
… There is a work on close domain data to identify intent in chatbots [8]. It uses … Nigam, A., Sahare, P., Pandya, K.: Intent detection and slots prompt in a closed-domain chatbot … Mikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space …

Data Extraction and Preprocessing for Automated Question Answering Based on Knowledge Graphs
A Romanov, D Volchek, D Mouromtsev – World Conference on Information …, 2020 – Springer
… Depending on the application context, such systems are called a dialog interface, question-answering system, or chatbot … idea of the algorithm is to represent the triples (h, r, t) of the set \(\mathcal {S}\) in a certain vector space of dimension … 1. Dale, R.: The return of the chatbots …

Target Guided Emotion Aware Chat Machine
W Wei, J Liu, X Mao, G Guo, F Zhu, P Zhou… – arXiv preprint arXiv …, 2020 – arxiv.org
… end, it is highly valuable and desirable to develop an emotion-aware chatbot that is … which takes account of static graph attention to incorporate commonsense knowledge for chatbots [54] … where E? is the ?-dimensional vector space of the emotions (? represents the number of …

Reply Using Past Replies—A Deep Learning-Based E-Mail Client
Y Feng, MA Naeem, F Mirza, A Tahir – Electronics, 2020 – mdpi.com
… but are also suited for short-text prediction scenarios, such as Chatbots used in … The vectorised document refers to the vector space model, which allows calculation of the … was successfully introduced from the field of machine translation into the Chatbot dialogue system [26], we …

A Robotic Dating Coaching System Leveraging Online Communities Posts
S Jo, D Jung, K Kim, EG Joung, G Nespoli… – arXiv preprint arXiv …, 2020 – arxiv.org
… Then, after tokenization with KoNLPY [12], titles are embedded in 256 dimension vector space with distributed memory … “Response selection with topic clues for retrieval-based chatbots.” Neurocomputing 316 … “Docchat: An information retrieval approach for chatbot engines using …

Embeddings in Natural Language Processing: Theory and Advances in Vector Representations of Meaning
MT Pilehvar… – Synthesis Lectures on …, 2020 – morganclaypool.com
… Conversational AI: Dialogue Systems, Conversational Agents, and Chatbots Michael McTear 2020 … Spoken Dialogue Systems Kristiina Jokinen and Michael McTear 2009 … The book starts by explaining conventional word vector space models and word embeddings (eg …

Progress in neural NLP: modeling, learning, and reasoning
M Zhou, N Duan, S Liu, HY Shum – Engineering, 2020 – Elsevier
… the dominating approach for NLP tasks, such as MT, machine reading comprehension (MRC), chatbot, and so … how to better model the context information in multi-turn tasks such as chatbots and dialog … For example, in the dialog system for custom service, the error or loss is not …

Conversational Scaffolding: An Analogy-based Approach to Response Prioritization in Open-domain Dialogs.
W Myers, T Etchart, N Fulda – ICAART (2), 2020 – gsc.npa.mybluehost.me
… Ontbot: Ontology based chatbot. In International Symposium on Inno- vations in Information and Communications Technol- ogy, pages 7–12. Banchs, RE and Li, H. (2012). Iris: a chat-oriented di- alogue system based on the vector space model …

A Deep Multi-task Model for Dialogue Act Classification, Intent Detection and Slot Filling
M Firdaus, H Golchha, A Ekbal, P Bhattacharyya – Cognitive Computation, 2020 – Springer
… To create robust human/machine dialogue systems or chatbots, it is essential to understand the … in [58, 66, 74] to complete the different modules of a dialogue system that can … For dialogue systems, especially for goal-oriented systems, the second step in dialogue processing is …

Chatterbot implementation using Transfer Learning and LSTM Encoder-Decoder Architecture
KB Prakash, YVR Nagapawan, NL Kalyani… – International …, 2020 – researchgate.net
… a modern Transfer-Transfo method, for conversational generative data-driven systems such as chatbots … The proposed model of the chatbot is done using the Sequence to Sequence … Term Embedding is a technique to achieve dense term representation in a small vector space …

Developing a Twitter bot that can join a discussion using state-of-the-art architectures
YM Çetinkaya, ?H Toroslu, H Davulcu – Social Network Analysis and Mining, 2020 – Springer
… Holotescu (2016) is an online course recommender system based on the user’s social media profile and interests serving on Facebook Messenger as a chatbot. Task-oriented chatbots provide service for a particular domain, where usually do not support open-ended …

Non?goal oriented dialogue agents: state of the art, dataset, and evaluation
A Mehndiratta, K Asawa – Springer
… The studies that present dialog systems or chatbots largely focus on techniques and designs around goal-oriented dialogue agents (Abdul-Kader et al … Words in a language are represented as real-valued vectors, also known as word embeddings, in a vector space …

An Automatic Question Answering Method for Small-Scale Corpus
Y Shao, G Xu, M Xu, L Dong – Journal of Physics: Conference …, 2020 – iopscience.iop.org
… This article uses XML language to store the dialog system intent recognition template, as shown in figure 2 … [4] Wang H and Li B 2018 Research progress of chatbot system Computer … [12] Li L and Li H 2018 Computing text similarity based on concept vector space Data Analysis …

Seq2Seq AI Chatbot with Attention Mechanism
A Sojasingarayar – arXiv preprint arXiv:2006.02767, 2020 – arxiv.org
… Most of this chatbots are developed for the restricted domain … Word Embedding is a technique for learning dense representation of words in a low dimensional vector space … Also, due to lack of real-life quality data the chatbot performed somehow below optimum for imitating …

Utility of Neural Embeddings in Semantic Similarity of Text Data
M Hendre, P Mukherjee, M Godse – Evolution in Computational …, 2020 – Springer
… In tasks like sentiment analysis, chatbot, question answering, automatic essay evaluation, dialog systems, parsing, word … https://doi.org/10.18653/v1/K16-1006. 6. Mikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient Estimation of Word Representations in Vector Space …

Text Messaging-Based Medical Diagnosis Using Natural Language Processing and Fuzzy Logic
NAI Omoregbe, IO Ndaman, S Misra… – Journal of Healthcare …, 2020 – hindawi.com
The use of natural language processing (NLP) methods and their application to developing conversational systems for health diagnosis increases patients’ access to medical knowledge. In this study, a chatbot service was developed for the Covenant University Doctor (CUDoctor …

Intent Mining from past conversations for Conversational Agent
A Chatterjee, S Sengupta – arXiv preprint arXiv:2005.11014, 2020 – arxiv.org
… has been a growing community and business interest in conversational systems (chatbots primarily) and … is a type of supervised training mechanism, which is supported by many commercial chatbot building frameworks … ous vector space where similar words are mapped together …

Optimising User Experience with Conversational Interface
CA Iglesias – … 2020: Workshop Proceedings of the 16th …, 2020 – books.google.com
… The main goal was to implement a scalable, easily main- tainable chatbot, which interacts … that’s why machine learning techniques holds such potential in the area of chatbots … Model Initially introduced in Efficient Estimation of Word Representations in Vector Space [11], where …

Chatbot Designing Information Service for New Student Registration Based on AIML and Machine Learning
Y Wijaya, F Zoromi – JAIA-Journal of Artificial Intelligence and …, 2020 – jurnal.sar.ac.id
… The tower takes input and implements it into the semantic vector space (vectors R and C in the … Students Page Prospective student pages consist of only one view, the ChatBot view, which is the interface that Prospective Students will use when interacting with chatbots …

Designing and Implementing Adaptive Bot Model to Consult Ethiopian Published Laws Using Ensemble Architecture with Rules Integrated
H Asimare – 2020 – ir.bdu.edu.et
… about the rest of knowledge. Goal-oriented dialog systems are those different systems clearly … chatbots) … Based on “Donna Interactive Chat-bot acting as a Personal Assistant” the conversational bots can be used as virtual assistance …

INTELLECTUAL TEXTS PROCESSING IN SOCIO-ECONOMIC APPLICATIONS
SD Belov, IS Kadochnikov, VV Korenkov, PV Zrelov – ceur-ws.org
… Chatbots made up approximately 20 % of tweets about the 2016 us presidential election [2, 3]. These … Response generation is, to a different extent, inherent in all types of dialog systems, some types … The main idea of the vector space model (VSM) is to represent each text of the …

Reasoning in Dialog: Improving Response Generation by Context Reading Comprehension
X Chen, Z Cui, J Zhang, C Wei, J Cui, B Wang… – arXiv preprint arXiv …, 2020 – arxiv.org
… Lan- guage Processing due to its broad application prospect, in- cluding chatbots, virtual personal … To make appropriate responses, dialogue systems must be equipped with the ability to understand … hot representation of each word in X, Q, into a high- dimensional vector space …

CHAPTER FOUR DISTRIBUTIONAL AND NETWORK SEMANTICS. TEXT ANALYSIS APPROACHES ALEXANDER KHARLAMOV, DENIS GORDEEV AND DMITRY …
A KHARLAMOV – Neuroinformatics and Semantic …, 2020 – books.google.com
… So, the best chat-bot of 2007 UltraHal1 used not only search by key … Open domain-Closed domain -General purpose AI ELIZA -Task oriented modern chat-bots Automated attendants … com/@ madrugado/what-are-the-dialog-systems-or-something- about-eliza-9aefb551eaaa …

Dynamic word recommendation to obtain diverse crowdsourced paraphrases of user utterances
MA Yaghoub-Zadeh-Fard, B Benatallah… – Proceedings of the 25th …, 2020 – dl.acm.org
… 1 INTRODUCTION Dialog systems (also known as virtual assistants, conversational agents, chatbots or simply … For example Microsoft’s chatbot Tay, which quickly made a number of racist, sexist, and … Word embedding methods map words into a vector space model in a way that …

Enhancing sentient embodied conversational agents with machine learning
D Tellols, M Lopez-Sanchez, I Rodríguez… – Pattern Recognition …, 2020 – Elsevier
… In fact, the mounting interest in chatbots has been accompanied by the emergence of a number of tools for chatbot development, including DialogFlow from Google, wit.ai from Facebook, Watson Assistant from IBM, and LUIS from Microsoft. 4 …

A Conceptual IR Chatbot Framework with Automated Keywords-based Vector Representation Generation
AS Lokman, MA Ameedeen… – IOP Conference Series …, 2020 – iopscience.iop.org
… 2.2. Response Generation Two basic methods for chatbots to generate/produce a response are … WE) or vector representation of word are real numbers in vector space that can … Chatbot enhanced algorithms: a case study on implementation in Bahasa Malaysia human language …

Techniques Comparison for Natural Language Processing
O Iosifova, I Iosifov, O Rolik, V Sokolov – researchgate.net
… tagging, information retrieval, summarization, question answering, dialog systems building, and many more … and different by meaning groups of words should be separable in vector space … modifications) with attention eg, for intent classification in widespread chatbot frame- works …

Learning an Effective Context-Response Matching Model with Self-Supervised Tasks for Retrieval-based Dialogues
R Xu, C Tao, D Jiang, X Zhao, D Zhao… – arXiv preprint arXiv …, 2020 – arxiv.org
… Building an intelligent dialogue system with the ability to select a proper response according to a multi-turn context is a great … Besides, the response retrieved from existing dialogue systems super- vised by the conventional way still faces some critical challenges, including …

End to End Speech Recognition Error Prediction with Sequence to Sequence Learning
P Serai, A Stiff, E Fosler-Lussier – ICASSP 2020-2020 IEEE …, 2020 – ieeexplore.ieee.org
… Such approaches have found success in machine translation [1, 2] and dialog systems tasks [3 … pled decoding for adapting a text-based chatbot answer pre- diction system to work … embedding to encode semantic meaning and word confusability in the same vector space, so as to …

A Response Retrieval Approach for Dialogue Using a Multi-Attentive Transformer
MA Senese, A Benincasa, B Caputo… – arXiv preprint arXiv …, 2020 – arxiv.org
… 2020. Towards a human-like open- domain chatbot. arXiv preprint arXiv:2001.09977 … Overview of the ninth dialog system technology challenge: Dstc9. He, K.; Gkioxari, G.; Dollár, P.; and Girshick, R. 2017 … Ef- ficient estimation of word representations in vector space …

Simple and principled uncertainty estimation with deterministic deep learning via distance awareness
JZ Liu, Z Lin, S Padhy, D Tran, T Bedrax-Weiss… – arXiv preprint arXiv …, 2020 – arxiv.org
… In the weather-service chatbot example, the out- of-domain space XOOD = X /XIND is the space of all natural utterances not related to … can be well- separated by a set of linear decision boundaries, and sentences encoders aim to project sentences into a vector space where the …

A light method for data generation: a combination of Markov Chains and Word Embeddings
E Martínez Garcia, A Nogales, J Morales Escudero… – 2020 – rua.ua.es
… of augmenting a corpus used to build a Language Model (LM) that will help to tune chatbots designed for a … generated by our method by including them in a reranking procedure for generating the answer of a chatbot … Efficient estimation of word representations in vector space …

Sequential neural networks for noetic end-to-end response selection
Q Chen, W Wang – Computer Speech & Language, 2020 – Elsevier
… to-end response selection challenge as one track in the 7th Dialog System Technology Challenges … of the art of utterance classification for real world goal-oriented dialog systems, for which … models (Serban et al., 2016), building an end-to-end dialogue system became feasible …

Incorporating Politeness across Languages in Customer Care Responses: Towards building a Multi-lingual Empathetic Dialogue Agent
M Firdaus, A Ekbal, P Bhattacharyya – Proceedings of The 12th …, 2020 – aclweb.org
… Such systems are highly prevalent nowadays in the form of chatbots and personal assistants like Ap … language generation is one of the core components of every dialogue system (Shen et al … embed- dings for Hindi and English are mapped in the same vector space using linear …

Heterogeneous Relational Reasoning in Knowledge Graphs with Reinforcement Learning
M Saebi, S Krieg, C Zhang, M Jiang… – arXiv preprint arXiv …, 2020 – arxiv.org
… of large-scale knowledge graphs (KG), relational reasoning addresses a number of important applications, such as question answering [30,3], dialogue systems [20,18 … and deep learning approaches [1,26,27,7,33,4]. These methods embed the KG into a vector space and use a …

An intelligent Chatbot using deep learning with Bidirectional RNN and attention model
M Dhyani, R Kumar – Materials Today: Proceedings, 2020 – Elsevier
… A thought vector is a vector space containing sequence of numbers which represent meaning of the sentence … For example, Erica, which is a Chatbot, is Bank of America’s AI virtual assistant, which … The e-market and Retail Chatbots make engaging environment for users to shop …

Empathetic dialogue generation using generation-based models
E Zaranis – 2020 – dspace.lib.ntua.gr
… ??????? ???????- ???????? ??? ?????? ???? ??? ??? ???????? ???? ?????????. ?? ????? chatbot ??? ??????????? ????????? ?? ??????? ???? ?? ELIZA. ??????, ???????? ???????? chatbots ?????????? ?????? ??? 8 Page 9 …

Adaptive dialogue management using intent clustering and fuzzy rules
D Griol Barres, Z Callejas Carrión, JM Molina… – 2020 – digibug.ugr.es
… in mobile devices and smart speakers, educational tutoring agents, entertainment chatbots in open … to represent documents using vectors and calculate distances in the vector space model using … Let’s Go is a spoken dialogue system developed by the Carnegie Mellon University …

DECiSION: Data-drivEn Customer Service InnovatiON
M de Gemmis, D Primiceri, S Lisi, M Casaburi, G Basile… – researchgate.net
… The project foresees the implementation of a chatbot, which acts as a virtual assistant, and a … h”, gives the answer in a simple and effective way through mobile applications, chatbots or user … of words [8] starting from a non-annotated corpus and building a vector space in which …

Efficacy of Deep Neural Embeddings based Semantic Similarity in Automatic Essay Evaluation
M Hendre, P Mukherjee, R Preet… – International Journal of …, 2020 – journal.uob.edu.bh
… In tasks like sentiment Analysis, Chatbot, Question Answering, Automatic Essay Evaluation, Dialogue Systems, Parsing, Word … DOI 10.18653/v1/K16-1006 [19] Mikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space …

DECiSION: Data-drivEn Customer Service InnovatiON
D Esposito, M Polignano, P Basile… – … Science and Its …, 2020 – Springer
… The project foresees the implementation of a chatbot, which acts as a virtual assistant, and a … h”, gives the answer in a simple and effective way through mobile applications, chatbots or user … of words [8] starting from a non-annotated corpus and building a vector space in which …

Selection and Generation: Learning towards Multi-Product Advertisement Post Generation
Z Chan, Y Zhang, X Chen, S Gao, Z Zhang… – Proceedings of the …, 2020 – aclweb.org
… To begin with, we obtain the post topic T and the product candidate set P. More details of these symbols are mentioned in Section 3. First, we use an embedding matrix e to embed each word in T and P into a high-dimensional vector space …

Phoneme based Domain Prediction for Language Model Adaptation
A Bhasin, G Mathur, P Yenigalla… – 2020 International Joint …, 2020 – ieeexplore.ieee.org
… I. INTRODUCTION Voice based interaction with smart devices is becoming popular for example Chatbot applications and personal assistants … [15] T. Mikolov, K. Chen, G. Corrado, & J. Dean, “Efficient Estimation of Word Representations in Vector Space,” In Proceedings of …

Do We Need Online NLU Tools?
P Lorenc, P Marek, J Pichl, J Konrád… – arXiv preprint arXiv …, 2020 – arxiv.org
… a specific field of text classification, intent recognition is a core component of dialogue systems [29 … Dataset Intent Train Test Chatbot FindConnection 57 71 Corpus DepartureTime 43 35 TOTAL 100 … the proper size of the vector space [1]. The next reason is strongly practical—we …

Conversational agent with common-sense: Responding to nonsensical statements
AP Konar – 2020 – era.library.ualberta.ca
… Conversational agents fall into two categories Open Domain chatbots and Goal-oriented chatbots. An Open Domain chatbot can have conversations with humans about a vast array of topics; it has a wide range of knowledge and mimics human-like …

Intent Detection Problem Solving via Automatic DNN Hyperparameter Optimization
J Kapo?i?t?-Dzikien?, K Balodis, R Skadi?š – Applied Sciences, 2020 – mdpi.com
… Usually, chatbots are composed of the following components: natural language understanding (NLU … management (responsible for a fluent conversation), content (responsible for chatbot’s properly selected … of user questions is the core of smooth operation in any dialog system …

Deep AM-FM: Toolkit for Automatic Dialogue Evaluation
C Zhang, LF D’Haro, RE Banchs, T Friedrichs… – … Dialogue Systems for the …, 2020 – Springer
… We primarily discuss the application of deep learning techniques in vector-space representations of … evaluating text generation tasks in NLP, such as machine translation, dialogue system and text … C, Li H (2019) Automatic evaluation of end-to-end dialog systems with adequacy …

A Design Science Research to Correct Inherent Biases in Natural Language Applications
J Manseau, I Mbuko – 2020 – core.ac.uk
… provide a purposeful artifact to take biases into account for the development of chatbots and AI … “Ethical Challenges in Data-Driven Dialogue Systems.” Proceedings of … K., Corrado, G., and Dean, J. 2013 “Efficient estimation of word representations in vector space.” arXiv preprint …

ScriptWriter: Narrative-Guided Script Generation
Y Zhu, R Song, Z Dou, JY Nie, J Zhou – arXiv preprint arXiv:2005.10331, 2020 – arxiv.org
… 2.2 Dialogue Systems … This is a new problem that has not been studied before. Contrary to open-domain chatbots, task-oriented systems are designed to accomplish tasks in a spe- cific domain (Seneff et al., 1998; Levin et al., 2000; Wang et al., 2011; Tur and Mori, 2011) …

A multiparty chat-based dialogue system with concurrent conversation tracking and memory
VR Martinez, J Kennedy – Proceedings of the 2nd Conference on …, 2020 – dl.acm.org
… INTRODUCTION Bohus and Horvitz [4] recognized that “most spoken dialog system research could … this was recorded successfully in the previous interaction, the dialogue system will automatically … machine learning framework for building contex- tual AI assistants and chatbots …

A prior case study of natural language processing on different domain
J Shruthi, S Swamy – International Journal of Electrical and …, 2020 – search.proquest.com
… The presenting chatbot technique follow the statement of text information that’s text by user in the form of … It can be utilized as a text interface or like a linguistic dialog system … c. Vector Quantization (VQ): The VQ is a procedure for mapping vectors from a big vector space to a …

A prior case study of natural language processing on different domain.
S Swamy – International Journal of Electrical & Computer …, 2020 – search.ebscohost.com
… The presenting chatbot technique follow the statement of text information that’s text by user in the form of … It can be utilized as a text interface or like a linguistic dialog system … c. Vector Quantization (VQ): The VQ is a procedure for mapping vectors from a big vector space to a …

From Eliza to Siri and Beyond
L Coheur – … on Information Processing and Management of …, 2020 – Springer
… Within hours of being in use, the chatbot was racist, nazi and vulgar, and had to … T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space … Pereira, MJ, Coheur, L., Fialho, P., Ribeiro, R.: Chatbots’ greetings to human-computer communication …

Can You be More Social? Injecting Politeness and Positivity into Task-Oriented Conversational Agents
YC Wang, A Papangelis, R Wang, Z Feizollahi… – arXiv preprint arXiv …, 2020 – arxiv.org
… Chat- bots are designed to have more socially-oriented chit chat with users … some researchers have studied how to incorporate social language into chatbots to generate … For example, XiaoIce, Microsoft’s social chatbot in China, can respond with empathetic language and show …

Natural Language Generation
C Room – algorithms, 2020 – devopedia.org
… NLG , along with NLU , is at the core of chatbots and voice assistants. A familiar example might be Gmail’s Smart Compose … All words are represented individually in the vector space instead of reducing them to a single fixed-length vector …

Matching Questions and Answers in Dialogues from Online Forums
Q Jia, M Zhang, S Zhang, KQ Zhu – arXiv preprint arXiv:2005.09276, 2020 – arxiv.org
… Online Forums Qi Jia 1 and Mengxue Zhang 1 and Shengyao Zhang 1 and Kenny Q. Zhu 2 Abstract. Matching question-answer relations between two turns in conversations is not only the first step in analyzing dialogue structures, but also valuable for training dialogue systems …

Impact of Users’ Beliefs in Text-Based Linguistic Interaction
V Catania, S Monteleone, M Palesi, D Patti – IEEE Access, 2020 – ieeexplore.ieee.org
… [21] J. Huang, M. Zhou, and D. Yang, ”Extracting chatbot knowledge from … G. Vassallo, and S. Gaglio, ”A semantic layer on semi-structured data sources for intuitive chatbots,” in Proc … RE Banchs and H. Li, ”Iris: A chat-oriented dialogue system based on the vector space model,” in …

Named entity recognition and relation detection for biomedical information extraction
N Perera, M Dehmer, F Emmert-Streib – Frontiers in Cell and …, 2020 – frontiersin.org
… The word vectors position themselves in the vector space, such that words with a common contextual meaning are closer to each other … The contextual distance among words creates a linear sub-structural pattern in the vector space, as defined by logarithmic probability …

A Novel Multi-agent-based Chatbot Approach to Orchestrate Conversational Assistants
JF Zolitschka – International Conference on Business Information …, 2020 – Springer
… Therefore, we rely on the vector space representation and apply the preprocessing agent insofar as … 212–225 (2017)Google Scholar. 5. Dhanda, S.: How chatbots will transform the retail … 2018)Google Scholar. 6. Abdul-Kader, SA, Woods, JC: Survey on chatbot design techniques …

Would you Like to Talk about Sports Now? Towards Contextual Topic Suggestion for Open-Domain Conversational Agents
A Ahmadvand, H Sahijwani, E Agichtein – Proceedings of the 2020 …, 2020 – dl.acm.org
… tasks and challenges have been proposed to push the boundaries of conversational AI to de- velop more intelligent chatbots to carry … agent that coherently and engagingly converses with humans on a variety of topics, remains an aspirational goal for dialogue systems [33, 40] …

Neural Discourse Modelling of Conversations
JM Pierre – Available at SSRN 3663042, 2020 – papers.ssrn.com
… interest in conversational user interfaces such as virtual assistants and chatbots, the application of … J. Dean, (2013) “Efficient estimation of word representations in vector space”, arXiv preprint … A large dataset for research in unstructured multi-turn dialogue systems”, arXiv preprint …

ODO: Design of Multimodal Chatbot for an Experiential Media System
R Bhushan, K Kulkarni, VK Pandey, C Rawls… – Multimodal …, 2020 – mdpi.com
… both a software and hardware level. In this paper, we explicate the design of our chatbot and its interface with the larger system, and discuss the key insights into artistic deployment of such chatbots. In particular, we focus on the …

Natural language processing: an overview
H Amini, F Farahnak, L Kosseim – Frontiers, 2020 – World Scientific
… Conversational Agents (also known as dialogue systems) are applica- tions that are able to hold coherent conversations with humans … Two types of conversational agents have been developed: task-oriented bots and chatbots …

Automatic Labeled Dialogue Generation for Nursing Record Systems
T Mairittha, N Mairittha, S Inoue – Journal of Personalized Medicine, 2020 – mdpi.com
… As we can see, well-known chatbot platforms (eg, Amazon Lex (https://aws.amazon.com … First, we explain the basic concept of a task-oriented dialogue system, NLU components, and … of the words, sentence embeddings propose to embed a whole sentence into a vector space …

NLP for the Greek Language: A Brief Survey
K Papantoniou, Y Tzitzikas – 11th Hellenic Conference on Artificial …, 2020 – dl.acm.org
… [78] describes a vector space model where … 3.7 Pragmatics (Dialogue Systems) Pragmatic analysis attempts to put each sentence into its general situational context, taking into … The thesis [38] describes a conversational chatbot system based on public services for a greek web …

A Survey of Knowledge-Enhanced Text Generation
W Yu, C Zhu, Z Li, Z Hu, Q Wang, H Ji… – arXiv preprint arXiv …, 2020 – arxiv.org
… text to include salient information; question answering (QA) generates textual answers to given questions; dialogue system supports chatbots to communicate … For example, in dialogue systems, conditioning on only the input text, a text generation system often produces …

Topic-Guided Relational Conversational Recommender in Multi-Domain
L Liao, R Takanobu, Y Ma, X Yang… – … on Knowledge and …, 2020 – ieeexplore.ieee.org
… questions about whether a user likes an item or whether the user prefers an item to another, while a typical task oriented dialogue system often directly … There are also another line of approaches using reinforcement learning (RL) to train goal-oriented dialogue systems [11], [25] …

Experience grounds language
Y Bisk, A Holtzman, J Thomason, J Andreas… – arXiv preprint arXiv …, 2020 – arxiv.org
Page 1. Experience Grounds Language Yonatan Bisk* Ari Holtzman* Jesse Thomason* Jacob Andreas Yoshua Bengio Joyce Chai Mirella Lapata Angeliki Lazaridou Jonathan May Aleksandr Nisnevich Nicolas Pinto Joseph Turian Abstract …

Better cooperation through communication in multi-agent reinforcement learning
I Kiseliou – 2020 – diva-portal.org
… For instance, supervised text-based and speech dialogue systems (chatbots) have become near-ubiquitous in … techniques can be employed to mitigate these shortcomings by exposing chatbots to the … a look-up table, mapping the agent’s hand to a game-specific vector space; is …

Diving Deep into Deep Learning: History, Evolution, Types and Applications
HCA Deekshith Shetty, MJ Varma, S Navi, MR Ahmed – researchgate.net
… natural language processing. which uses external components like Word2vec, where it converts a corpus of words into vectors which can be thrown into a vector space to measure their similarity [42]. Generative adversarial …

Employing Abstract Meaning Representation to Lay the Last-Mile Toward Reading Comprehension
B Galitsky – Artificial Intelligence for Customer Relationship …, 2020 – Springer
… Note the difference between the similarity of Q to A expressed in a vector space versus expressed as a maximum common sub-graph, obtained via generalization (Galitsky 2012). 3.6 Syntactic Generalization. We show examples …

Natural Language Processing Advancements By Deep Learning: A Survey
A Torfi, RA Shirvani, Y Keneshloo, N Tavvaf… – arXiv preprint arXiv …, 2020 – arxiv.org
… The bag-of-words model [40], often viewed as the vector space model, involves a representation which accounts only for the words and their frequency of occurrence. BoW ignores the order and interaction of words, and treats each word as a unique feature …

Employing a Transformer Language Model for Information Retrieval and Document Classification: Using OpenAI’s generative pre-trained transformer, GPT-2
A Bjöörn – 2020 – diva-portal.org
… One will be a vector space model based on TF- IDF (term frequency-inverse document frequency) and will … “Enriching Conversation Context in Retrieval-based Chatbots” by Tahami … Used BERT [20] to construct a retrieval-based dialogue system, ie a dialogue system based on …

Developing Amaia: A Conversational Agent for Helping Portuguese Entrepreneurs—An Extensive Exploration of Question-Matching Approaches for Portuguese
J Santos, L Duarte, J Ferreira, A Alves, HG Oliveira – Information, 2020 – mdpi.com
… 2. Related Work. Dialogue systems typically exploit large collections of text, often including conversations … In opposition to generative systems, IR-based dialogue systems do not handle very well requests for which there is no similar text in the corpus …

Infusing Multi-Source Knowledge with Heterogeneous Graph Neural Network for Emotional Conversation Generation
Y Liang, F Meng, Y Zhang, J Xu, Y Chen… – arXiv preprint arXiv …, 2020 – arxiv.org
… Then, we apply a position-wise feed forward network FFN(?) (Vaswani et al. 2017) to project Gf to tex- tual vector space Xf as follows: Xf = FFN(Gf ), Xf ? RN×df , where df is the dimension of facial expression node rep- resentation …

Conversational Chatbots with Memory-based Question and Answer Generation
M Lundell Vinkler, P Yu – 2020 – diva-portal.org
… The other chatbot type is for entertainment, conversation, building a relationship and such, hence usually carry on … It is an attractive solution as it allows for the creation of chatbots simply by … in the same context, which then leads to the words being closer together in vector space …

A Question Answering System For Interacting with SDMX Databases
G Thiry, I Manolescu, L Liberti – The 6 Natural Language Interfaces for the …, 2020 – hal.inria.fr
… It consists of 12 files and about 1800 lines of code; it is available online at https://github.com/guillaume-thiry/OECD- Chatbot. The … similarity. 8 Related work Chatbots have become ubiquitous tools for human-computer interaction [11] …

Learning to Respond with Your Favorite Stickers: A Framework of Unifying Multi-Modality and User Preference in Multi-Turn Dialog
S Gao, X Chen, L Liu, D Zhao, R Yan – arXiv preprint arXiv:2011.03322, 2020 – arxiv.org
… where they predict the probable emoji given the contextual information from multi-turn dialog systems … 49, 56, 62], machine translation [51], text summarization [9, 23, 39], dialog system [11, 76 … representation of each word in each utterance ?? to a high-dimensional vector space …

Teaching Machines to Converse
J Li – arXiv preprint arXiv:2001.11701, 2020 – arxiv.org
… conventional dialog systems still face a variety of major challenges such as robustness … measurements (eg, vector space models or TF-IDF), page-rank style relatedness propaga … to endow a dialogue system with a consistent element of identity or persona (background …

How natural language processing can be used to improve digital language learning
H Kakavandy, J Landeholt – 2020 – diva-portal.org
… effectively be used for text classification, similarity measurement and learning from dialogue systems, all of … to specific system utterances, that is, questions and expressions by the chat bot need to be … that with a large corpus of English learner’s responses, a vector space made up …

You May Like This Hotel Because…: Identifying Evidence for Explainable Recommendations
S Kanouchi, M Neishi, Y Hayashibe, H Ouchi… – Proceedings of the 1st …, 2020 – aclweb.org
… 1 Introduction Recently, dialog systems using Natural Lan- guage Processing technology have been adopted in interactive services such as call centers (Zumstein and Hundertmark, 2017). One challenging issue in a real-world scenario is vague requests1 from users …

Relationship Identification Between Conversational Agents Using Emotion Analysis
S Qamar, H Mujtaba, H Majeed, MO Beg – Cognitive Computation – Springer
… Smart chatbots deployed as helpline agents on Twitter are prime examples of such a use-case … Recent generative conversational models have been incorporating audio features for incorporating such sentiments in dialog systems [41] …

Proverb representation using semantic technologies: a case study of Nigerian Yoruba proverbs
VA Omolaoye – 2020 – ir.nust.na
… 75 76 FIGURE 18: SEQUENCE DIAGRAM OF USER INTERACTION WITH SYSTEM 76 FIGURE 19: CHATBOT INTERFACE 76 … OPM – Object Process Paradigm PARADISE – PARAdigm for DIalogue System Evaluation POS – Part of Speech PWS – Possible World Semantic …

A deep learning-based multi-turn conversation modeling for diagnostic Q&A document recommendation
Z Yang, W Xu, R Chen – Information Processing & Management – Elsevier
… In brief, the three main contributions of our research work are summarized as follows. First, many studies focus on modeling multi-turn conversations to help build a dialog system but neglect recommendations for diagnostic multi-turn Q&A …

A Socially-Aware Conversational Recommender System for Personalized Recipe Recommendations
F Pecune, L Callebert, S Marsella – Proceedings of the 8th International …, 2020 – dl.acm.org
… ?),?(? )?. Each ingredient of the Food Database is repre- sented in the same vector space and ingredients are sorted by the distance of their vector to ?, with the closest ingredient as the first one of the list. Ingredients that the …

Affective and Human-Like Virtual Agents
B Budnarain – 2020 – uwspace.uwaterloo.ca
… recent years. It should be noted that dialogue systems are also referred to as conversational agents or chatbots. From an alternative perspective, dialogue systems can be viewed as intelligent virtual assistive technology [14]. AI …

Advanced Semantics for Commonsense Knowledge Extraction
TP Nguyen, S Razniewski, G Weikum – arXiv preprint arXiv:2011.00905, 2020 – arxiv.org
… and their prop- erties is useful for AI applications such as robust chatbots … Dialogue systems should not just generate plausible utterances from a language model, but should … addition, we leverage WordNet to distinguish antonyms, with which vector space embeddings typically …

Generating Responses that Reflect Meta Information in User-Generated Question Answer Pairs
T Kodama, R Higashinaka, K Mitsuda… – Proceedings of The …, 2020 – aclweb.org
… question-answering 1. Introduction Much attention has been paid to non-task oriented dialogue systems from their social and entertainment aspects (Wal- lace, 2009; Banchs and Li, 2012; Higashinaka et al., 2014). To make …

Learning to Respond with Stickers: A Framework of Unifying Multi-Modality in Multi-Turn Dialog
S Gao, X Chen, C Liu, L Liu, D Zhao… – Proceedings of The Web …, 2020 – dl.acm.org
… are mostly based on emoji recommendation, where they predict the probable emoji given the contextual informa- tion from multi-turn dialog systems … an embedding matrix e to map a one-hot representation of each word in each utteranceui to a high-dimensional vector space …

Example Phrase Adaptation Method for Customized, Example-Based Dialog System Using User Data and Distributed Word Representations
N Kitaoka, E Seto, R Nishimura – IEICE Transactions on Information …, 2020 – jstage.jst.go.jp
… There have been many studies on example-based spo- ken dialog systems … con- texts of words by using vectors to represent words in a 200- dimensional vector space … KITAOKA et al.: EXAMPLE PHRASE ADAPTATION METHOD FOR EXAMPLE-BASED DIALOG SYSTEM …

Practical Natural Language Processing: A Comprehensive Guide to Building Real-World NLP Systems
S Vajjala, B Majumder, A Gupta, H Surana – 2020 – books.google.com
… 81 Vector Space Models 84 Basic Vectorization Approaches 85 One-Hot Encoding 85 Bag of … A Simple FAQ Bot A Taxonomy of Chatbots Goal-Oriented Dialog Chitchats A Pipeline for Building Dialog Systems Dialog Systems in Detail PizzaStop Chatbot Deep Dive …

Creative Storytelling with Language Models and Knowledge Graphs
X Yang, I Tiddi – CIKM (Workshops), 2020 – openreview.net
… The blue arrows indicate the workflow of the language fine-tuning process. quality and relevance. Similarly, Zhou et al. (2020) re- sort to a knowledge graph that consists of a collection of head-relation-tail triples to retrieve related topics in their intelligent dialogue system …

Detecting Abuse on the Internet: It’s Subtle
S Bagga – 2020 – search.proquest.com
Page 1. Detecting Abuse on the Internet: It’s Subtle Sunyam Bagga Master of Science School of Computer Science McGill University Montreal, Quebec December, 2019 A thesis submitted to McGill University in partial fulfillment …

Spoken Dialogue for Social Robots
T Kawahara, K Jokinen – interspeech2020.org
… Page 2. Spoken Dialogue Systems (SDS) are prevailing • Smartphone Assistants … Keeping engagement • Can be done without robots/agents (cf.) chatbot • Will be more engaging with robots/agents 24 … ASR engine Architecture of Spoken Dialogue System (SDS) 48 Page 42 …

The B-Subtle framework: tailoring subtitles to your needs
M Ventura, J Veiga, L Coheur, S Gama – Language Resources and …, 2020 – Springer
… Banchs, R., Li, H. (2012). IRIS: a chat-oriented dialogue system based on the vector space model. In Proc … Serban, IV, Sordoni, A., Bengio, Y., Courville, AC, & Pineau, J. (2016). Building end-to-end dialogue systems using generative hierarchical neural network models …

A deep look into neural ranking models for information retrieval
J Guo, Y Fan, L Pang, L Yang, Q Ai, H Zamani… – Information Processing …, 2020 – Elsevier

New Avenues in Mobile Tourism
C Guerreiro, E Cambria… – 2020 International Joint …, 2020 – ieeexplore.ieee.org
… Unlike e-commerce or retail brands using chatbots, which can appear gimmicky, there is … Consequently, a chatbot like Skyscanner is able to cut through the noise, connecting … Sentic medoids: Organizing affective common sense knowledge in a multi-dimensional vector space …

A CONTEMPORARY SURVEY ON INTELLIGENT HUMAN-ROBOT INTERFACES FOCUSED ON NATURAL LANGUAGE PROCESSING
I Giachos, D Piromalis, M Papoutsidakis, S Kaminaris… – 2020 – researchgate.net
… robot on a campus (Chen et al., 2019 ), an Augmented Robotic Dialog System, which is … (2015) on the creation of an Augmented Robot Dialogue System (ARDS), for … constitutes a powerful client–server environment for implementing and running spoken dialogue systems; so it …

Service skill improvement for home robots: Autonomous generation of action sequence based on reinforcement learning
M Zhang, G Tian, Y Zhang, P Duan – Knowledge-Based Systems – Elsevier
… For instance, Cuayahuitl proposed a novel approach for training reinforcement learning based chatbots, together with an interesting reward functions to address the lacking of well-embraced metrics for measuring chatbot performance [40] …

Automating Question Generation Given the Correct Answer
H Cao – 2020 – diva-portal.org
Page 1. DEGREE PROJECT IN COMPUTER SCIENCE AND ENGINEERING, SECOND CYCLE, 30 CREDITS STOCKHOLM, SWEDEN 2020 Automating Question Generation Given the Correct Answer HAOLIANG CAO KTH ROYAL INSTITUTE OF TECHNOLOGY …

DEEP NEURAL NETWORK MODELS FOR SEQUENCE LABELING AND COREFERENCE TASKS
BM Sergeevich – mipt.ru
… them, aiming at building a set of pre-trained network models, predefined dialogue system components and pipeline templates … 86 3.9 Annotating step of a voice-enabled chatbot. . . . . 88 … 1966 ELIZA ELIZA was one of the earliest chatbots, developed by Joseph …

Cluster-based information retrieval using pattern mining
Y Djenouri, A Belhadi, D Djenouri, JCW Lin – Applied Intelligence, 2020 – Springer
This paper addresses the problem of responding to user queries by fetching the most relevant object from a clustered set of objects. It addresses the commo.

Dialogue-Based Relation Extraction
D Yu, K Sun, C Cardie, D Yu – arXiv preprint arXiv:2004.08056, 2020 – arxiv.org
… However, these methods may be insufficient for powering a number of practical real-time dialogue- based applications such as chatbots, which would likely require recognition of a relation at its first mention in an interactive conversation …

Feasibility and usability of MentorPal, a framework for rapid development of virtual mentors
BD Nye, DM Davis, SZ Rizvi, K Carr… – Journal of Research …, 2020 – Taylor & Francis
… topics (t). Dialog classifier optimization. The quality of the dialog system was tested formatively and revised, using a combination of machine learning metrics (eg, cross-validation, test sets) and formative user testing. While the …

Nowcasting in chatbot design: Leveraging service journey patterns to improve user satisfaction
Y Wang, Y Wang, X Luo – 2020 – papers.ssrn.com
… Furthermore, while existing research documented a series of benefits of proactive chatbots, such as making … current chatbot is organized into a hierarchical categorization with 7 layers … layer to learn the latent representational vector space spanned by the questions. In the …

Deep Learning for Text Attribute Transfer: A Survey
D Jin, Z Jin, R Mihalcea – arXiv preprint arXiv:2011.00416, 2020 – arxiv.org
Page 1. Deep Learning for Text Attribute Transfer: A Survey Di Jin? MIT CSAIL jindi15@mit.edu Zhijing Jin* Max Planck Institute zjin@tuebingen.mpg.de Rada Mihalcea University of Michigan mihalcea@umich.edu Abstract …

Proceedings of The 12th Language Resources and Evaluation Conference
N Calzolari, F Bechet, P Blache, K Choukri… – Proceedings of The …, 2020 – aclweb.org
Page 1. LREC 2020 Marseille TWELFTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION May 11-16 , 2020 PALAIS DU PHARO Marseille, France CONFERENCE PROCEEDINGS Editors …

SUMBT+ LaRL: End-to-end Neural Task-oriented Dialog System with Reinforcement Learning
H Lee, S Jo, HJ Kim, S Jung, TY Kim – arXiv preprint arXiv:2009.10447, 2020 – arxiv.org
… D- dimensional vector space Em ? RK×D. Therefore, the sampled discrete latent variables zm are then mapped into the vector space using their … C. End-to-End Neural Task-Oriented Dialog Systems The first end-to-end trainable task-oriented dialog system framework was …

Query Intent Detection from the SEO Perspective
S Mohammadi, M Chapon, A Frémond – European Conference on …, 2020 – Springer
… in Natural Language Processing (NLP) tasks such as question answering, chatbots, and search … the synonyms and related words closer to each other in the vector space and moving … J., Li, Y., Lin, M.: Review of intent detection methods in the human-machine dialogue system …

Neural Question Generation with Transfer Learning and Utilization of External Knowledge
M Delpisheh – 2020 – yorkspace.library.yorku.ca
… The generated QAs can be useful for training deep neural network models for building eg, dialog systems. QG can also benefit reading comprehension (Du, Shao, and Cardie, 2017), self … accomplish a task (eg, dialogue systems, summarization). Therefore, by considering …

World Knowledge Representation
Z Liu, Y Lin, M Sun – Representation Learning for Natural Language …, 2020 – Springer
… learning in KGs aims to project both entities and relations into a low-dimensional continuous vector space to get … with the learned knowledge representations widely utilized in various knowledge-driven tasks like question answering, information retrieval, and dialogue system …

Dialog Response Generation Using Adversarially Learned Latent Bag-of-Words
K Khan – 2020 – uwspace.uwaterloo.ca
Page 1. Dialog Response Generation Using Adversarially Learned Latent Bag-of-Words by Kashif Khan A thesis presented to the University of Waterloo in fulfillment of the thesis requirement for the degree of Master of Mathematics in Computer Science …

Response Generation Using Large-scale Pre-trained Language Models
J Nyberg – 2020 – diva-portal.org
… applied to the field of language processing, for purposes such as chatbots or translators … The robot has conversational capabilities, using an existing semi-automatic dialog system, and interacts … Their solution is instead to map textual input to a vector space representing emotions …

Biomedical Text Dependency Parsing with the Neural Turku Parser
T Ngo Minh – 2020 – doria.fi
… a very long research tradition, and while it is usually not seen as a stand-alone applica- tion, it is an essential building block for many other NLP tasks, for example machine translation (Galley and Manning, 2009) and dialogue system (Sugiyama et al., 2013). In …

Augmenting Small Data to Classify Contextualized Dialogue Acts for Exploratory Visualization
A Kumar, B Di Eugenio, J Aurisano… – Proceedings of The 12th …, 2020 – aclweb.org
… Available public datasets on dialogue are limited to a few domains, mostly chatbots or informa- tion search … In spoken dialogue systems, seman- tic slot filling is tasked with identifying terms belonging to fixed slots and passing them as parameters to down-stream processing …

Exploiting Text Matching Techniques for Knowledge-Grounded Conversation
Y Ahn, SG Lee, J Park – IEEE Access, 2020 – ieeexplore.ieee.org
… Now, we introduce shallow matching-based networks and three of our implementations of remarkable models in response selection for retrieval-based chatbot. We choose the models according to their representativeness and perfor- mance in the given topic …

A comprehensive review on feature set used for anaphora resolution
K Lata, P Singh, K Dutta – Artificial Intelligence Review, 2020 – Springer
In linguistics, the Anaphora Resolution (AR) is the method of identifying the antecedent for anaphora. In simple terms, this is the problem that helps to s.

Suicidal ideation detection in online social content
S Ji – 2020 – researchgate.net
… which was later discontinued because of privacy issues. The latter is a Facebook chatbot based on … 2.3a and 2.3b, respectively. To apply DNNs, natural language text is usually embedded into distributed vector space Page 17. 2.1. METHODS AND CATEGORIZATION 9 …

Integration of Fuzzy Logic in Analogical Reasoning: A Prototype
M Colombo, S D’Onofrio… – 2020 IEEE 16th …, 2020 – ieeexplore.ieee.org
… D’Onofrio, “From Simple Question-Answering Systems to “Intelligent” Chatbots – A Conceptual … Intelligence and Analogical Reasoning to Smartify Web-based Dialogue Systems,” PhD Thesis … J. Dean, “Efficient estimation of word representations in vector space,” In Proceedings …

Modelling speaker adaptation in second language learner dialogue
AJ Sinclair – 2020 – era.ed.ac.uk
… While this adapta- tion is natural to humans, it is an open problem for dialogue systems, where managing … An example of this constrained style of interaction was Duolingo’s chat-bot, which allowed the user to participate in a heavily scripted dialogue with constrained text en

A Systematic Review of Automatic Question Generation for Educational Purposes
G Kurdi, J Leo, B Parsia, U Sattler… – International Journal of …, 2020 – Springer
While exam-style questions are a fundamental educational tool serving a variety of purposes, manual construction of questions is a complex process that req.

Conversational User Interfaces on Mobile Devices: Survey
R Jaber, D McMillan – Proceedings of the 2nd Conference on …, 2020 – dl.acm.org
… 1chatbot, conversational interface, speech interface, voice user interface, intelligent personal assistant, conversational agent, conversational user interface, voice assistant, anthropomorphism, conversation analysis, conversational AI, social robot, dialog systems, smart speaker …

A Companion Robot for Modeling the Expressive Behavior of Persons with Parkinson’s Disease
AP Valenti – 2020 – search.proquest.com
… 107 Chapter 6 Improving Natural Language Understanding in Spoken Dialogue Systems 109 6.1 Introduction … xix Page 21. 6.1 Typical components of a spoken dialogue system. At each turn t, input speech is converted to an utterance, ut, which the Natural Lan …

Designers characterize naturalness in voice user interfaces: their goals, practices, and challenges
Y Kim – 2020 – open.library.ubc.ca
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