Cosine Similarity & Dialog Systems 2017


Notes:

  • Conversational system

Resources:

Wikipedia:

References:

See also:

Language Computer Corporation (LCC)Lexical Chain & Dialog SystemsLSM (Latent Semantic Mapping)NLP Tools & Dialog SystemsNLTK & Dialog SystemsOpenEphyra (Ephyra Question Answering System)Porter StemmerQuora & Natural Language ProcessingTweetNLP


Training end-to-end dialogue systems with the ubuntu dialogue corpus
RT Lowe, N Pow, IV Serban, L Charlin… – Dialogue & …, 2017 – dad.uni-bielefeld.de
… selection, and natural language generator model are all com- bined, this can also be seen as a form of end-to-end dialogue system … (2014) whose model, although rule-based, is not composed of modules, as it retrieves a response to the context based on cosine similarity …

Active learning for example-based dialog systems
T Hiraoka, G Neubig, K Yoshino, T Toda… – Dialogues with Social …, 2017 – Springer
… 1. Calculate the similarity \(\mathrm{sim}(u_{i}, u)\) between all example inputs \(u_{i}\) in D, and input u. This is often defined as tf-idf weighed cosine similarity [20] … [8] and evaluate the dialog system with test examples (right side of Fig …

The fourth dialog state tracking challenge
S Kim, LF D’Haro, RE Banchs, JD Williams… – Dialogues with Social …, 2017 – Springer
… the challenge included a series of optional pilot tracks for the core components in developing end-to-end dialog systems using the … AM-FM: Weighted mean of (1) the cosine similarity between the system generated utterance and the reference utterance and (2) the normalized n …

Using Summarization to Discover Argument Facets in Online Ideological Dialog
A Misra, P Anand, JEF Tree, M Walker – arXiv preprint arXiv:1709.00662, 2017 – arxiv.org
… Amita Misra, Pranav Anand, Jean Fox Tree, and Marilyn Walker UC Santa Cruz Natural Language and Dialogue Systems Lab 1156 N. High … We used cosine similarity as the distance measure with average link- age criteria …

Measuring the similarity of sentential arguments in dialog
A Misra, B Ecker, MA Walker – arXiv preprint arXiv:1709.01887, 2017 – arxiv.org
… Amita Misra, Brian Ecker, and Marilyn A. Walker University of California Santa Cruz Natural Language and Dialog Systems Lab 1156 N … For each argument, we ex- tract the unigrams, bigrams and trigrams, and then calculate the cosine similarity between two texts represented as …

Building Task-Oriented Dialogue Systems for Online Shopping.
Z Yan, N Duan, P Chen, M Zhou, J Zhou, Z Li – AAAI, 2017 – aaai.org
… System Formalization Formally, a task-oriented dialogue system consists of the fol- lowing four main components: DS = {QU, ST , DM, PKB} … We then compute a similarity score between Q and each product category Ci by measuring the cosine similarity between their semantic …

A conditional variational framework for dialog generation
X Shen, H Su, Y Li, W Li, S Niu, Y Zhao… – arXiv preprint arXiv …, 2017 – arxiv.org
… Deep latent variable models have been shown to facilitate the response generation for open-domain dialog systems … evaluations (aver- age, greedy and extrema) (Liu et al., 2016) on all our models, which map responses into vector space and compute the cosine similarity …

Relevance of unsupervised metrics in task-oriented dialogue for evaluating natural language generation
S Sharma, LE Asri, H Schulz, J Zumer – arXiv preprint arXiv:1706.09799, 2017 – arxiv.org
… Ad- versarial methods might be promising for task- oriented dialogue systems but more research needs to be conducted on their account … We consider another set of metrics which compute the cosine similarity between the embeddings of the predicted and the reference …

Deconvolutional paragraph representation learning
Y Zhang, D Shen, G Wang, Z Gan… – Advances in Neural …, 2017 – papers.nips.cc
… a required first step toward more applied tasks, such as sentiment analysis [1, 2, 3, 4], machine translation [5, 6, 7], dialogue systems [8, 9 … the latent vector h is fed through a multi-layer deconvolutional decoder with stride to reconstruct X as ˆX, via cosine-similarity cross-entropy …

Is this a child, a girl or a car? Exploring the contribution of distributional similarity to learning referential word meanings
S Zarrieß, D Schlangen – Proceedings of the 15th Conference of the …, 2017 – aclweb.org
… Sina Zarrieß and David Schlangen Dialogue Systems Group // CITEC // Faculty of Linguistics and Literary Studies Bielefeld University, Germany {sina.zarriess,david … objects into w and ¬w instances, we label each object with a real- valued similarity obtained from cosine similarity …

Hyponym/hypernym detection in science and technology thesauri from bibliographic datasets
T Kawaumra, M Sekine… – … Computing (ICSC), 2017 …, 2017 – ieeexplore.ieee.org
… The types and degrees of the semantic relations among terms are calculated by cosine similarity using the distances between the vectors corresponding to the terms … Thus, the two relations are difficult to distinguish by the cosine similarity …

Sequence Adversarial Training and Minimum Bayes Risk Decoding for End-to-end Neural Conversation Models
W Wang, Y Koji, BA Harsham, T Hori… – … of the 6th Dialog System …, 2017 – merl.com
… Finally, the objective function based on adversarial training and the cosine similarity achieved the best human rating score 3.4777. 5. Conclusion We proposed a neural conversation system for the 6th Dialog System Technology Challenge (DSTC6) …

Adversarial evaluation for open-domain dialogue generation
E Bruni, R Fernández – Proceedings of the 18th Annual SIGdial Meeting …, 2017 – aclweb.org
… We also observe that, while there is a tendency to higher cosine similarity in the ground-truth positive in- stances than in the negative ones … How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Met- rics for Dialogue Response Generation …

Predicting emotional word ratings using distributional representations and signed clustering
J Sedoc, D Preo?iuc-Pietro, L Ungar – … of the 15th Conference of the …, 2017 – aclweb.org
… Inferring the emotional content of words is important for text-based sentiment anal- ysis, dialogue systems and psycholinguis- tics, but word ratings … between words i and j incorporate both the signed information and the word similarities computed using the cosine similarity of the …

Definition Modeling: Learning to Define Word Embeddings in Natural Language.
T Noraset, C Liang, L Birnbaum, D Downey – AAAI, 2017 – aaai.org
… We compare against models from previ- ous work on the reverse dictionary task (Hill et al. 2016). The previous models read a definition and output an embed- ding, then use cosine similarity between the output embed- ding and the word embedding as a ranking score …

Utterance Retrieval based on Recurrent Surface Text Patterns
GD Duplessis, F Charras, V Letard, AL Ligozat… – … on Information Retrieval, 2017 – Springer
… The main goal is to provide a dialogue system with the ability to appropriately react to a large variety of unexpected out-of-domain human … The most common ones are vector-space models at the token level along with the cosine similarity [2] and classic Term Frequency-Inverse …

Sequential Dialogue Context Modeling for Spoken Language Understanding
A Bapna, G Tur, D Hakkani-Tur, L Heck – Proceedings of the 18th …, 2017 – aclweb.org
… (Dhingra et al., 2016) show improved performance on an informational dialogue agent by incorporating knowledge base context into their dialogue system … 104 Page 3. Figure 3: Architecture of the dialogue context encoder for the cosine similarity based memory network …

Event-based knowledge reconciliation using frame embeddings and frame similarity
M Alam, DR Recupero, M Mongiovi, A Gangemi… – Knowledge-Based …, 2017 – Elsevier
… In order to find the similarity between two frames and between two roles, this study uses WordNet similarities and cosine similarity for obtaining better consolidation between … [33,34] apply Frame Semantics and Distributional Semantics for slot filling in Spoken Dialogue System …

DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset
Y Li, H Su, X Shen, W Li, Z Cao, S Niu – arXiv preprint arXiv:1710.03957, 2017 – arxiv.org
… 1 Introduction Developing intelligent chatbots and dialog systems is of great significance to both commercial and aca- demic camps … We measure the distance between embed- dings as the average of cosine similarity, Jaccard distance and Euclidean distance …

Data Distillation for Controlling Specificity in Dialogue Generation
J Li, W Monroe, D Jurafsky – arXiv preprint arXiv:1702.06703, 2017 – arxiv.org
… A good dialogue system should have the ability to decide when to say generic things and when not to … in the training data to each highly frequent response from the list L and assign a relevance score R(e) to each training example e based on the cosine similarity between e and …

Multimodal Dialogs (MMD): A large-scale dataset for studying multimodal domain-aware conversations
A Saha, M Khapra, K Sankaranarayanan – arXiv preprint arXiv:1704.00200, 2017 – arxiv.org
… Specifically, we compute the cosine similar- ity between the learnt image embedding and the encoded representation of the multimodal context. The model is then trained to maximize the margin between the cosine similarity for the correct image and the incorrect images. Fig …

A Unified Model for Cross-Domain and Semi-Supervised Named Entity Recognition in Chinese Social Media.
H He, X Sun – AAAI, 2017 – aaai.org
… Sun, Kashima, and Ueda (2013) used Gaussian RBF and poly- nomial kernels to compute task similarity; Bhatt, Semwal, and Roy (2015) used cosine similarity measure to compute similarity for domain adaption. Semi-Supervised Learning …

Neural Matching Models for Question Retrieval and Next Question Prediction in Conversation
L Yang, H Zamani, Y Zhang, J Guo, WB Croft – arXiv preprint arXiv …, 2017 – arxiv.org
… VSM: is method computes the cosine similarity between the TF-IDF representation of the given two sequences … In many question answering and chatbot/dialogue systems, new questions issued by users have no explicit prede ned category …

Affective Neural Response Generation
N Asghar, P Poupart, J Hoey, X Jiang, L Mou – arXiv preprint arXiv …, 2017 – arxiv.org
… As will be shown in the experiments, these affective strategies can be combined to further improve Seq2Seq dialogue systems … where sim(·) denotes a similarity measure between two vec- tors. In our experiments, we use the cosine similarity func- tion …

Edina: Building an Open Domain Socialbot with Self-dialogues
B Krause, M Damonte, M Dobre, D Duma… – arXiv preprint arXiv …, 2017 – arxiv.org
… Our focus on data collection stems from the scarcity of publicly available corpora for training dialogue systems. During the first stage of the competition, we surveyed the corpora mentioned in Serban et al … 6 Page 7. Dividing Sc i by ? would yield a cosine similarity based score …

Obtaining referential word meanings from visual and distributional information: Experiments on object naming
S Zarrieß, D Schlangen – … of 55th annual meeting of the …, 2017 – pub.uni-bielefeld.de
… Sina Zarrieß and David Schlangen Dialogue Systems Group // CITEC // Faculty of Linguistics and Literary Studies Bielefeld University, Germany {sina.zarriess … into w and ¬w instances, we label each object with a real-valued similarity obtained from cosine similarity between w …

Neural response generation via gan with an approximate embedding layer
Z Xu, B Liu, B Wang, SUN Chengjie, X Wang… – Proceedings of the …, 2017 – aclweb.org
… Lintean, 2012). Alternatively, an utterance representation can be obtained by averaging the embeddings of all the words in that utterance, of which the cosine similarity gives the Average metric (Mitchell and Lapata, 2008). In …

Semantic mapping of natural language input to database entries via convolutional neural networks
M Korpusik, Z Collins, J Glass – Acoustics, Speech and Signal …, 2017 – ieeexplore.ieee.org
… Hierarchical ABCNN applies cosine similarity attention between CNN representations of a query and each sentence in a document for machine comprehension [22] … [5] M. Korpusik and J. Glass, “Spoken language understanding in a nutrition dialogue system,” ASLP, Submitted …

Semantic specialisation of distributional word vector spaces using monolingual and cross-lingual constraints
N Mrkši?, I Vuli?, DÓ Séaghdha, I Leviant… – arXiv preprint arXiv …, 2017 – arxiv.org
… To the best of our knowledge, this is the first work on multilingual training of any compo- nent of a statistical dialogue system … synonymy pair (xl,xr), the negative example pair (tl,tr) is chosen from the remain- ing in-batch vectors so that tl is the one closest (cosine similarity) to xl …

A Knowledge Enhanced Generative Conversational Service Agent
Y Long, J Wang, Z Xu, Z Wang… – … the 6th Dialog System …, 2017 – workshop.colips.org
… 4.1. Automatic Evaluation The proposed dialog systems are first automatically evaluated by several word-overlap metrics, including BLEU, METEOR … met- rics firstly approximate response embeddings based on word embedding, and then calculate cosine similarity between the …

Eliciting Positive Emotional Impact in Dialogue Response Selection
N Lubis, S Sakti, K Yoshino, S Nakamura – uni-ulm.de
… Lasguido et al. have previously examined the utilization of cosine similarity for response retrieval in an example-based dialogue system [8]. In their approach, the similarity is computed between TF-IDF weighted term vectors of the query and the examples …

Information Navigation System with Discovering User Interests
K Yoshino, Y Suzuki, S Nakamura – … of the 18th Annual SIGdial Meeting …, 2017 – aclweb.org
… News texts collected from a Kyoto prefec- ture sightseeing Web site3 was used as the training data of word2vec, LSTM-based encoder-decoder model, and content of the dialogue system. We used cosine similarity between the vectors of doc- uments to calculate the similarities …

Dialogue Breakdown Detection based on Estimating Appropriateness of Topic Transition
H Sugiyama – workshop.colips.org
… It is difficult for the current dialogue systems to continue outputting appro- priate responses, and thus utterances that cause the dialogue to collapse … The word similarities are calculated with three types of methods: the cosine similarity of the bag-of-word vectors, the word mover’s …

Dialog-Based Interactive Movie Recommendation: Comparison of Dialog Strategies
H Mori, Y Chiba, T Nose, A Ito – International Conference on Intelligent …, 2017 – Springer
… Figure 1 shows an overview of an example-based spoken dialog system. When a user inputs a sentence, the system determines an example sentence in the database that is most similar to the input sentence. We used word-based cosine similarity as the similarity …

A “small-data”-driven approach to dialogue systems for natural language human computer interaction
T Boros, SD Dumitrescu – Speech Technology and Human …, 2017 – ieeexplore.ieee.org
… A scenario is the equivalent of a frame in a in frame-based dialogue system, but by default we don’t … TABLE I COSINE SIMILARITY BETWEEN WORDS USING WORD-EMBEDDINGS COMPUTED FROM THE ROMANIAN WIKIPEDIA DUMP CORPUS Romanian word Details Cos …

Argumentative dialogue system based on argumentation structures
R Higashinaka, K Sakai, H Sugiyama… – Proc. SEMDIAL 2017 …, 2017 – isca-speech.org
… Figure 2 shows the overall architecture of our ar- gumentative dialogue system … The similarity is calculated using the cosine similarity be- tween the sentence vectors created from the averaged word vectors of the statement of an argumentation node and a user utterance …

A Context Based Dialog System with a Personality
A Choudhary, V Kalingeri – pdfs.semanticscholar.org
… is a harder problem for sequence to sequence model, we hypothesize that this is be- cause the sentence pairs for our dialog system re- lies … We con- struct a matrix of cosine similarity between the persona vectors of the characters Joey, Chandler, Ross, Phoebe, Monica, Rachel …

Intension Classification of User Queries in Intelligent Customer Service System
S Song, H Chen, Z Shi – researchgate.net
… Query intention classification in QA system can also be taken as Dialogue Intention Recognition (DIR) [5], and in dialogue systems, understanding user … of an query q with linear combination of vectors of all words in q, and then calculate query similarity with cosine similarity [7]. 3 …

Utterance Intent Classification of a Spoken Dialogue System with Efficiently Untied Recursive Autoencoders
T Kato, A Nagai, N Noda, R Sumitomo, J Wu… – Proceedings of the 18th …, 2017 – aclweb.org
… No 0.6 No way. freq. : relative frequency distribution in percent. 2 Spoken Dialog System on Smartphone … prec. recall acc. (1) Cosine similarity of bag-of-words (BoW) – – – 76.0% 74.2% 85.1% (2) Tied RAE based on random word vectors 37.2% 33.2% 70.6% 32.0% 65.6% 66.4 …

Development of An Arabic Conversational Intelligent Tutoring System for Education of Children with ASD
SS Aljameel, JD O’Shea, KA Crockett… – Computational …, 2017 – ieeexplore.ieee.org
… The utterance is not recognised by the PM approach, whereas when the system applied the Cosine similarity algorithm, the utterance is recognised … [25] T. Bickmore and T. Giorgino, “Health dialog systems for patients and consumers,” Journal of biomedical informatics, vol …

Collaboration-based User Simulation for Goal-oriented Dialog Systems
D Didericksen, ORKSL Zhou, J Kramer – alborz-geramifard.com
… Increasing contextual similarity accuracy: we use a cosine similarity between tf-idf repre- sentations of the last utterances to measure the contextual similarity … [2] S. Young, M. Gašic, B. Thomson, and JD Williams. POMDP-based statistical spoken dialog systems: A review …

RUCIR at the NTCIR-13 STC-2 Task
Y Zhu, X Wang, X Zuo, S Lu, Z Ma, X Zhang, Z Dou – research.nii.ac.jp
… Common retrieval-based dialog systems work in a 1To make it clearly, we use STC-1 to denote the STC task in NTCIR-12 and STC-2 for NTCIR-13 … The first one is the Cosine similarity between the gen- erated reply and corresponding post …

Alquist: An Open-Domain Dialogue System
J Pichl – radio.feld.cvut.cz
… 9https://aws.amazon.com/dynamodb/ Page 4. 4 J. Pichl, Alquist Dialogue System The personal information module does not require to be processed by the automaton … We take the cosine similarity between TF-IDF vectors as a score. 3.6. Generative Networks …

Building Emotional Conversation Systems Using Multi-task Seq2Seq Learning
R Zhang, Z Wang, D Mai – National CCF Conference on Natural Language …, 2017 – Springer
… (1). where \(\lambda \) is set to 0.5. \(S_{topic}\) is topic similarity calculated by the LDA model and \(S_{cosine}\) is cosine similarity defined as … References. 1. André, E., Rehm, M., Minker, W., Bühler, D.: Endowing spoken language dialogue systems with emotional intelligence …

Are Word Embedding and Dialogue Act Class-based Features Useful for Coreference Resolution in Dialogue?
S Agrawal, A Joshi, JC Ross, P Bhattacharyya… – cse.iitb.ac.in
… semantic agree Semantic class agreement semantic distance ment, semantic distance sent Cosine similarity between average word vectors Dialog-specific features is same speaker … [6] discusses a coreference resolution system for a virtual patient dialogue system …

A retrieval-based dialogue system utilizing utterance and context embeddings
A Bartl, G Spanakis – arXiv preprint arXiv:1710.05780, 2017 – arxiv.org
… deep Recurrent Neural Networks, constituting all modules in one model [2], have become one of the major research topics for Dialogue Systems … scoring functions introduced in this section will solely be based on vector comparison metrics, such as the cosine similarity, as text …

KSU Team’s Dialogue System at the NTCIR-13 Short Text Conversation Task 2
Y Ishibashi, S Sugimoto, H Miyamori – pdfs.semanticscholar.org
Page 1. KSU Team’s Dialogue System at the NTCIR-13 Short Text Conversation Task 2 … However, it is not possible to use sentence generation al- gorithms using images for the dialogue systems since many text-based dialogue systems only accept text input …

Modeling Conversations to Learn Responding Policies of E2E Task-oriented Dialog System
Z Bai, B Yu, G Chen, B Wang, Z Wang – workshop.colips.org
… HRED model is further expanded by Serban et al. [11] for building dialog systems to predict the next utterance corresponding the entire dialog history … Word Embedding Word-level LSTM W11 W12 W1n Wm1 Wmn Relevance measured by cosine similarity u1 um Utterances …

User adaptation of input-response pairs in an example-based dialog system using distributed representation of words
E Seto, N Kitaoka – Advanced Informatics, Concepts, Theory …, 2017 – ieeexplore.ieee.org
… We then calculate the similarity between the selected words related to the user and words in the existing example phrases of the dialog system. Cosine similarity between the distributed representations of the nouns is calculated using the word2vec program …

Collection of Example Sentences for Non-task-Oriented Dialog Using a Spoken Dialog System and Comparison with Hand-Crafted DB
Y Kageyama, Y Chiba, T Nose, A Ito – International Conference on Human …, 2017 – Springer
… evaluation. 2 Examples Collection by Conversation with Spoken Dialog System. We prepared initial databases and started the example collection. The … utterance. The cosine similarity was used for the similarity calculation. The …

Learning and Reusing Dialog for Repeated Interactions with a Situated Social Agent
J Kennedy, I Leite, A Pereira, M Sun, B Li… – … on Intelligent Virtual …, 2017 – Springer
… 194 J. Kennedy et al. Page 4. Dialog system AMT Dialog executor Dialog graph Dialog learner … This cosine similarity metric is also used to determine whether what the user says is similar to any of the child nodes of the node used by the agent in the non-failure cases (see Fig …

Text-based Speaker Identification on Multiparty Dialogues Using Multi-document Convolutional Neural Networks
K Ma, C Xiao, JD Choi – Proceedings of ACL 2017, Student Research …, 2017 – aclweb.org
… Research on dialogue systems has also involved considerable efforts on speaker identi- fication, as it constitutes an important step in build- ing a more natural and human-like system (Raux et al., 2006 … Cosine similarity is used to locate the 15 nearest neighbors to each utterance …

Automatic Evaluation of Chat-oriented Dialogue Systems using Large-scale Multi-references
H Sugiyama, T Meguro, R Higashinaka – uni-ulm.de
… a rule-based conversational system that uses 149,300 rules (pattern-response pairs) written in AIML [8] and retrieves responses whose associ- ated patterns have the highest word-based cosine similarity to the … Page 7. Automatic Evaluation of Chat-oriented Dialogue Systems 7 …

Avoiding Echo-Responses in a Retrieval-Based Conversation System
D Fedorenko, N Smetanin, A Rodichev – arXiv preprint arXiv:1712.05626, 2017 – arxiv.org
… We use a cosine similarity as the output matching function … [3] Ryan Lowe, Nissan Pow, Iulian Serban, and Joelle Pineau. The ubuntu dialogue corpus: A large dataset for research in unstructured multi-turn dialogue systems. CoRR, abs/1506.08909, 2015 …

RSL17BD at DBDC3: Computing Utterance Similarities based on Term Frequency and Word Embedding Vectors
S Kato, T Sakai – workshop.colips.org
… Run 1 used the maximum cosine similarity and geometric mean; Run 3 used arithmetic mean instead; Run 2 utilised the cosine … Tsunomori, T. Taka- hashi, and N. Kaji, “Overview of dialogue breakdown detection challenge 3,” in Proceedings of Dialog System Technology Chal …

Hierarchical context supplementation for consecutive question answering
K Miyamoto, H Takeuchi, S Masuda… – Service Operations and …, 2017 – ieeexplore.ieee.org
… candidates. Dialog systems [4] allow users to define interactive dialog on the basis of a certain set of predefined rules or keywords … questions. We first applied TF-IDF-based cosine similarity [25] to show the distance on a keyword level (Fig …

Gbot at the NTCIR-13 STC-2 Task
H Zhang, T Guo, Y Lan, J Guo, J Li, X Cheng – research.nii.ac.jp
… We define the cosine similarity of X and G as a constraint function. consSIM(X, G)=1?cosine(Average(X), Average(G)) (6) … How not to evaluate your dialogue system: An empirical study of unsupervised evaluation metrics for dialogue response generation …

Comparing Approaches for Automatic Question Identification
A Maredia, K Schechtman, SI Levitan… – Proceedings of the 6th …, 2017 – aclweb.org
… speech corpora that are open-ended, yet topically con- strained, is increasingly popular for re- search in spoken dialogue systems and speaker … tions using strict string matches, (2) the ROUGE metric which is based on n-gram comparisons, (3) cosine similarity between word …

Cross-genre Document Retrieval: Matching between Conversational and Formal Writings
T Jurczyk, JD Choi – arXiv preprint arXiv:1707.04538, 2017 – arxiv.org
… (2011) presented a spoken dialogue system that extracts predicate-argument structures and uses them to ex- tract facts from news documents … For embedding, fc uses embed- dings to generate sum vectors from both sets and returns the cosine similarity of these two vectors …

Improving Frame Semantic Parsing with Hierarchical Dialogue Encoders
A Bapna, G Túr, D Hakkani-Túr, L Heck – arXiv preprint arXiv:1705.03455, 2017 – arxiv.org
… (Dhingra et al., 2016) show improved performance on an informational dialogue agent by incorpo- rating knowledge base context into their dialogue system … Page 3. Figure 3: Architecture of the dialogue context encoder for the cosine similarity based memory network …

Enriching confusion networks for post-processing
S Ghannay, Y Estève, N Camelin – International Conference on Statistical …, 2017 – Springer
… while \(L_{Sim}\) and \(A_{Sim}\) are respectively the linguistic and acoustic similarities computed with the cosine similarity applied to … Vigouroux, N., et al.: The French MEDIA/EVALDA project: the evaluation of the understanding capability of spoken language dialogue systems …

Building Chatbots from Forum Data: Model Selection Using Question Answering Metrics
M Boyanov, I Koychev, P Nakov… – arXiv preprint arXiv …, 2017 – pdfs.semanticscholar.org
… We evaluated our model intrinsically using BLEU as is traditionally done in dialog systems … method is the follow- ing: given a question, the seq2seq model produces an answer, which we compare to each of the an- swers in the thread, eg, using cosine similarity (see below for …

Breakdown Detector for Chat-Oriented Dialogue
T Horii, H Mori, M Araki – Dialogues with Social Robots, 2017 – Springer
… Recently proposed statistical utterance generation methods in chat-oriented dialogue systems (eg, [2]) have robust response generation functionalities … Context-level: cosine similarity between accumulated word vector of context and the word vector of the system utterance …

Which iR Model has a BetteR sense of huMoR? seaRch oveR a laRge collection of Jokes
B VV, B VA, M KI, B PI – dialog-21.ru
… Moreover, jokes that occasionally ap- pear during interaction can make appear dialog systems more human-like … The word2vec (Mikolov et al., 2013) method is a way to obtain word vectors such that semantically similar words have close vectors in terms of cosine similarity …

What’s Up, Doc? A Medical Diagnosis Bot
M Agrawal, J Cheng, C Tran – stanford.edu
… 2 Background There are a number of different paradigms for building dialog systems. According to Allen et Page 2 … 4.5 Cosine Similarity We also use cosine similarity of GloVe vectors to help map extracted symptom substrings to symp- toms in ApiMedic …

Soft Seeded SSL Graphs for Unsupervised Semantic Similarity-based Retrieval
A Srivastava, M Datt – Proceedings of the 2017 ACM on Conference on …, 2017 – dl.acm.org
… matching and ranking play a key role in various informa- tion retrieval and natural language understanding applications such as modern web search, dialogue systems, cross language … computes the cosine similarity of the context-sensitive representa- tion of the question pair …

A Chatbot by Combining Finite State Machine, Information Retrieval, and Bot-Initiative Strategy
S Yi, K Jung – sanghyunyi.ml
… steps. First, it searches top 3 documents base on cosine similarity between the query and the ‘Body’ of the data … In fact, it is impossible to keep all the conversation to be machine-initiative in general purpose dialogue system. However …

Hierarchical Module Classification in Mixed-initiative Conversational Agent System
SXY Suzanna, LL Anthony – Proceedings of the 2017 ACM on …, 2017 – dl.acm.org
… Our operational context is practical task-oriented dialog systems that interacts with real world users … Relation tuples were ex- tracted using Stanford OpenIE [1], and the closest matching entities in the knowledge base were retrieved using the cosine similarity of pre-trained …

Simulation-Based Usability Evaluation of Spoken and Multimodal Dialogue Systems
S Hillmann – 2017 – Springer
… Spoken and Multimodal Dialogue Systems Page 2 … xiii Page 14. maxðAÞ a ¼ maxðAÞ,8a, b 2 A : b a (returns the highest value a from tuple A) minðAÞ a ¼ minðAÞ,8a, b 2 A : a b(returns the lowest value a from tuple A) simcsðv jj wÞ Cosine similarity of the vectors v and w …

Learning Dynamic Memory Network with Two Views
CU Shin, JW Cha – workshop.colips.org
… The POMDP-based dialog system consists of a language understanding model for analyzing input utterances … Therefore, we measure cosine similarity between each of the candidates and the generated result and select one with the highest similarity as the correct answer. (10) …

Boosting a Rule-Based Chatbot Using Statistics and User Satisfaction Ratings
O Efraim, V Maraev, J Rodrigues – Conference on Artificial Intelligence …, 2017 – Springer
… far from the complexity of the many multidimensional evaluation frameworks that have been proposed over time to assess the subjective satisfaction or acceptance of users of dialogue systems, chiefly spoken … Finally, the two representations are compared using cosine similarity …

Miscommunication handling in spoken dialog systems based on error-aware dialog state detection
CH Wu, MH Su, WB Liang – EURASIP Journal on Audio, Speech, and …, 2017 – Springer
… Based on these observations, historical information is crucial to improve the performance of a dialog system [40, 44] … vector of the i-th sentence; \( {\delta}_m^i \) equals 1 if the m-th f m belongs to the i-th sentence S i ; otherwise it is set to 0. The cosine similarity measure was …

Collaborative Response Content Recommendation for Customer Service Agents
C Ma, P Guo, X Xin, X Ma, Y Liang, S Xing, L Li… – … Symposium on Neural …, 2017 – Springer
… 4.1 Dataset. The primary source of data for this work is the multi-turn (3 is minimum) dialogue records for one month in customer service dialogue system … TFIDF: Prediction is calculated by using cosine similarity of TFIDF between the context and response. 2 …

Style Transfer in Text: Exploration and Evaluation
Z Fu, X Tan, N Peng, D Zhao, R Yan – arXiv preprint arXiv:1711.06861, 2017 – arxiv.org
… putes cosine similarity between source language input and target language output. It gets sentence embedding by Sin- gular Value Decomposition (SVD), which trains source and target language together. RUBER (Tao et al. 2017) was pro- posed to evaluate dialog system, it …

Contextual and Feature-based Models by PolyU Team at the NTCIR-13 STC-2 Task
Y Li, H Su, W Li – research.nii.ac.jp
… We measure the distance between embeddings as the average of cosine similarity, Jaccard dis- tance and Euclidean distance … The ubuntu dialogue corpus: A large dataset for research in unstructured multi-turn dialogue systems. In SIGDIAL Conference, 2015 …

YJTI at the NTCIR-13 STC Japanese Subtask
T Shimizu – research.nii.ac.jp
… In this work, we demonstrate that a retrieval-based dialog system can be effective and that the combinations of two el- ements, a … The ranker evaluates the returned 200 replies considering the cosine similarity between vectors and two metadata attributes, Theme and Genre, and …

An Ensemble Approach to Conversation Generation
Y Zhuang, X Wang, H Zhang, J Xie, X Zhu – National CCF Conference on …, 2017 – Springer
… (2) Instead of using retrieval-based dialogue system for post-reranking, generated and retrieval utterances are fed to a linear ensemble model in our system … Hamming Distance, Cosine Similarity, N-Gram and Maximum Mutual Information are used in the ranker. 2.7 Ensemble …

” Having 2 hours to write a paper is fun!”: Detecting Sarcasm in Numerical Portions of Text
L Kumar, A Somani, P Bhattacharyya – arXiv preprint arXiv:1709.01950, 2017 – arxiv.org
… Finally, if no match is found, then the tweet is predicted as non-sarcastic. 4.2 Approach-2: Noun phrase cosine similarity matching … Therefore, Approach-2 relaxes the con- straint by using cosine similarity to match the phrases in the test tweet and the repository entry …

Programming bots by synthesizing natural language expressions into API invocations
S Zamanirad, B Benatallah, M Chai Barukh… – Proceedings of the …, 2017 – dl.acm.org
… model. The actual semantic similarity of -? S and -? Tk is computed using the cosine similarity metric [12] … V. RELATED WORK AND DISCUSSIONS There is a considerable body of research conducted on spoken dialog systems. Some …

Continuous Learning as a Service for Conversational Virtual Agents
S Agarwal, S Atreja, G Dasgupta – International Conference on Service …, 2017 – Springer
… The method findSimilarUtterances(u) finds the utterances that are textually similar to u based on Jaccard and cosine similarity … Particularly for dialog systems and conversation agents, [16, 19] exploited a combination of active and semi-supervised learning approach for better …

Detecting Hypernym/Hyponym in Science and Technology Thesaurus Using Entropy-Based Clustering of Word Vectors
T Kawamura, M Sekine, K Matsumura – International Journal of …, 2017 – World Scientific
… We then calculated the cosine similarity of all pairs and validated the statistically signi¯cant di®erences between the sets of cosine similarities by Welch’s t test … Thus, the two relations are di±cult to distinguish by the cosine similarity …

Not All Dialogues are Created Equal: Instance Weighting for Neural Conversational Models
P Lison, S Bibauw – arXiv preprint arXiv:1704.08966, 2017 – arxiv.org
… sources in the form of factual information or entity-grounded opinions, which is a important requirement for developing task-oriented dialogue systems … The matching score between the context and its re- sponse is then determined as the cosine similarity between the two vectors …

An iterative approach for the global estimation of sentence similarity
T Kajiwara, D Bollegala, Y Yoshida, K Kawarabayashi – PloS one, 2017 – journals.plos.org
… pairs from five different domains: news headlines (Head), image descriptions (Img), answer pairs from a tutorial dialogue system (Stud), answer … trained word embeddings (https://code.google. com/archive/p/word2vec/) trained using SGNS and use cosine similarity to compute …

Reconciling Event-Based Knowledge Through RDF2VEC
M Alam, DR Recupero, M Mongiovi, A Gangemi… – ceur-ws.org
… SensEmbed. [5] apply Frame Semantics and Distributional Semantics for slot filling in Spoken Dialogue System. In … inverse. Once the training is finished, the cosine similarity is computed between two frames and roles. 5 Evaluation The …

A Chatbot for Psychiatric Counseling in Mental Healthcare Service Based on Emotional Dialogue Analysis and Sentence Generation
KJ Oh, D Lee, B Ko, HJ Choi – Mobile Data Management (MDM …, 2017 – ieeexplore.ieee.org
… If the cosine similarity is high among the lexical morphemes, then the morphemes can replace the vocabularies each other … Based on the information, the purpose of the service is to develop a personalized dialog system that communicate emotionally with the user through text …

Helping Users Understand Privacy Notices with Automated Query Answering Functionality: An Exploratory Study
KM Sathyendra, A Ravichander, PG Story… – 2017 – reports-archive.adm.cs.cmu.edu
… Then, cosine similarity was used as the similarity metric to compute the similarity between question and question labels and the question was assigned the question label for which the similarity was highest. Preliminary Results …

Multiple-Weight Recurrent Neural Networks
Z Cao, L Wang, G De Melo – Proceedings of the 26th International Joint …, 2017 – ijcai.org
… For dialogue systems, contextual information and dialogue interactions be- tween speakers are important signals … 3. Character to word embedding: Here, we choose the loss function to be the cosine similarity of the ground truth word embedding and the one generated by our …

CLEF 2017 dynamic search lab overview and evaluation
E Kanoulas, L Azzopardi – CEUR Workshop Proceedings, 2017 – strathprints.strath.ac.uk
… been solved however is an open problem, while task-completion is not the only quality criterion of interest in the development of dialog systems … provided and com- pared it to the text used in each individual section of Wikipedia; it made use of the cosine similarity between the …

Generating Sentences by Editing Prototypes
K Guu, TB Hashimoto, Y Oren, P Liang – arXiv preprint arXiv:1709.08878, 2017 – arxiv.org
… The von- Mises Fisher distribution is a distribution over vec- tors with unit norm, with a mean µ and a precision ? such that the log-likelihood of drawing a vector decays linearly with the cosine similarity to µ. Let fnorm = f and fdir = f/fnorm …

Addressee and Response Selection in Multi-Party Conversations with Speaker Interaction RNNs
R Zhang, H Lee, L Polymenakos, D Radev – arXiv preprint arXiv …, 2017 – arxiv.org
… textual information to predict addressees as opposed to relying on acoustic signals or gaze information in multi- modal dialog systems (Jovanovic, Akker … the responding speaker ares) as the addressee and chooses the response to maxi- mize the tf-idf cosine similarity with the …

Production Ready Chatbots: Generate if not Retrieve
A Tammewar, M Pamecha, C Jain, A Nagvenkar… – arXiv preprint arXiv …, 2017 – arxiv.org
… For identifying a state we compute cosine similarity be- tween the input message and each of the phrases associated with all possible … We measure the performance of dialogue systems using percentage of chats that are com- pletely handled by the dialogue system, without any …

Are you asking the right questions? Teaching Machines to Ask Clarification Questions
S Rao – Proceedings of ACL 2017, Student Research …, 2017 – aclweb.org
… 3We measure the cosine similarity between the averaged word embeddings of the question and the edit … Finally, asking ques- tion is a natural component of dialog, and build- ing a collaborative dialog system that can naturally converse with a user is a broad long term goal. 34 …

User Intent Classification using Memory Networks: A Comparative Analysis for a Limited Data Scenario
A Bhardwaj, A Rudnicky – arXiv preprint arXiv:1706.06160, 2017 – arxiv.org
… Since the classifier is meant to serve as a module in a practical dialog system, it needs to be able to work with limited training data … The decision to use Euclidean distance (instead of, say, cosine similarity etc.) and min of distance (as opposed to an average etc.) was empirically …

Deep-Learning Based Automatic Spontaneous Speech Assessment in a Data-Driven Approach for the 2017 SLaTE CALL Shared Challenge
YR Oh, HB Jeon, HJ Song, BO Kang, YK Lee… – Proc. 7th ISCA … – slate2017.org
… first obtained from TextsRef . Then, a cosine similarity is calculated between the two vectors of the hidden state values of the encoder of a sentence-level model for the input text and each of TextsRef,prompt. Next, we obtain …

Dialogue Act Semantic Representation and Classification Using Recurrent Neural Networks
P Papalampidi, E Iosif, A Potamianos – SEMDIAL 2017 SaarDial, 2017 – academia.edu
… 1 Introduction Dialogue Act (DA) classification constitutes a ma- jor processing step in Spoken Dialogue Systems (SDS) assisting the understanding of user input … kj representative of the ith DA ti, normalized in the range 0 to 1 and d (kj, w) is the cosine similarity between the …

Discovering Stylistic Variations in Distributional Vector Space Models via Lexical Paraphrases
X Niu, M Carpuat – Proceedings of the Workshop on Stylistic Variation, 2017 – aclweb.org
… detecting and analyzing stylistic variations is becoming increas- ingly important, and is relevant to applications ranging from dialogue systems (Mairesse, 2008) to … of a word w by comparing its meaning to that of seed words of known formal- ity using cosine similarity (Turney and …

Detecting Egregious Conversations between Customers and Virtual Agents
T Sandbank, M Shmueli-Scheuer, D Konopnicki… – arXiv preprint arXiv …, 2017 – arxiv.org
… al., 2009) they developed a taxonomy of available measures for an end-user’s quality of experi- ence for multimodel dialogue systems, some of … each sentence by averaging the pre-trained embeddings5 of each word in the sentence, calculating the cosine similarity between the …

Reinforcement Learning with External Knowledge and Two-Stage Q-functions for Predicting Popular Reddit Threads
J He, M Ostendorf, X He – arXiv preprint arXiv:1704.06217, 2017 – arxiv.org
… (2016) introduce a neural network-based trainable dialogue system with a database operator module. Dhingra et al … Semantic similarity: we use the standard tf-idf (term-frequency inverse-document- frequency) (Salton and McGill, 1986) and compute cosine similarity scores …

Building Generalize QA System, SLR
M Zoaib, H Raza, H Shabbir, M Suleman, HA Asghar – researchgate.net
… Binkley [67] papers reviews six different information retrieval models: vector space model with cosine similarity, vector space model with weighted sum, latent semantic indexing, query likelihood model with Dirichlet smoothing, query likelihood model with linear smoothing, and …

Punny Captions: Witty Wordplay in Image Descriptions
A Chandrasekaran, D Parikh, M Bansal – arXiv preprint arXiv:1704.08224, 2017 – arxiv.org
… 8Two sentences are similar if the cosine similarity be- tween the average of the Word2Vec (Mikolov et al., 2013) representations of words in each sentence is ? 0.8 … 2016. A wizard-of-oz study on a non-task-oriented dialog systems that reacts to user engagement …

Incorporating loose-structured knowledge into conversation modeling via recall-gate LSTM
Z Xu, B Liu, B Wang, C Sun… – Neural Networks (IJCNN) …, 2017 – ieeexplore.ieee.org
… can be considered as pairs). (3) The final knowledge base is obtained according to the frequency of pairs and the cosine similarity between “entity” and “attribute” calculated by word vectors. Vectorization of Context Triggered …

A deep reinforcement learning chatbot
IV Serban, C Sankar, M Germain, S Zhang… – arXiv preprint arXiv …, 2017 – arxiv.org
… Dialogue Dialogue SYSTEM: Hi … First, a set of K model responses are retrieved from a dataset using cosine similarity between the current dialogue history and the dialogue history in the dataset based on bag-of-words TF-IDF Glove word embeddings (Pennington et al …

Towards Automatic Generation of Entertaining Dialogues in Chinese Crosstalks
S Du, X Wan, Y Ye – arXiv preprint arXiv:1711.00294, 2017 – arxiv.org
… It would be an ideal resource for studying humor in dialogue system … utterance; • IR-CXT: Retrieve the response which is most similar to the input utterance and three previous utterances of the input utterance; Similarity was calculated by comparing word-level cosine similarity …

Geometry of Compositionality.
H Gong, S Bhat, P Viswanath – AAAI, 2017 – aaai.org
… robust sentence embeddings (Et- tinger, Elgohary, and Resnik 2016) and we measure compo- sitionality by the cosine similarity between the … sarcasm and metaphor is of great impor- tance in language processing applications like text analy- sis, dialogue systems and sentiment …

End-to-End Offline Goal-Oriented Dialog Policy Learning via Policy Gradient
L Zhou, K Small, O Rokhlenko, C Elkan – arXiv preprint arXiv:1712.02838, 2017 – arxiv.org
… Companies are increasingly interested in building goal-oriented dialog systems for domains such as customer service and reservation systems … Example reward functions can include the semantic distance between the two utterances or simply the cosine similarity …

Assigning personality/identity to a chatting machine for coherent conversation generation
Q Qian, M Huang, X Zhu – arXiv preprint arXiv …, 2017 – pdfs.semanticscholar.org
… P(j|y,< k,v >)) ? cos(yj,v) (9) where cos(yj,v) denotes the cosine similarity be- tween a word in a response and a profile value. More elaborated techniques, for instance, lan- guage models, will be studied as future work. 3.7 Loss Function and Training …

Hybrid occupation recommendation for adolescents on interest, profile, and behavior
A Ochirbat, TK Shih, C Chootong, W Sommool… – Telematics and …, 2017 – Elsevier
… c ) of user c and ContentBasedOccupation ( s ) of occupation s can represent as TF-IDF vectors w ? c and w ? s of keyword weights, so can calculate score between ContentBaseProfile ( c ) and ContentBasedOccupation ( s ) by using cosine similarity [2] is given by …

General Pipeline Architecture for Domain-Specific Dialogue Extraction from different IRC Channels
A Abouzeid – 2017 – content.grin.com
… Improving Best Response in Unstructured Dialogue Systems Author: Ahmed Abouzeid … the unstructured ones. Recent advances in Data-Driven Dialogue Systems made use of the Ubuntu published IRC channel conversations to extract one-on-one dialogues …

Deep learning based recommender system: A survey and new perspectives
S Zhang, L Yao, A Sun – arXiv preprint arXiv:1707.07435, 2017 – arxiv.org
Page 1. 35 Deep Learning based Recommender System: A Survey and New Perspectives SHUAI ZHANG, University of New South Wales LINA YAO, University of New South Wales AIXIN SUN, Nanyang Technological University …

MUSE: Modularizing Unsupervised Sense Embeddings
GH Lee, YN Chen – arXiv preprint arXiv:1704.04601, 2017 – arxiv.org
… 1 Introduction Recently, deep learning methodologies have dom- inated several research areas in natural language processing (NLP), such as machine translation, language understanding, and dialogue systems. However …

An Empirical Study on Incorporating Prior Knowledge into BLSTM Framework in Answer Selection
Y Li, M Yang, T Zhao, D Zheng, S Li – National CCF Conference on …, 2017 – Springer
… Cosine similarity: question or answer is represented by VSM, and each word is weighted by TF*ISF, then calculate the cosine similarity between two vectors; … A comprehensive view demands further examination of this issue in other NLP tasks such as MT, dialogue system etc …

Knowledge Guided Short-Text Classification for Healthcare Applications
S Cao, B Qian, C Yin, X Li, J Wei… – Data Mining (ICDM) …, 2017 – ieeexplore.ieee.org
… As Fig. 1 shows, the chatbot faces a big challenge to determine the user’s intent in a typical dialog system if the utterance contains unrecognized entity words … Since we expect the latter embeddings to be distinguishable, we add a cosine similarity regularization term on it …

Integrating extra knowledge into word embedding models for biomedical nlp tasks
Y Ling, Y An, M Liu, SA Hasan, Y Fan… – … 2017 International Joint …, 2017 – ieeexplore.ieee.org
… We get vector representations from embedding models for both target word and candidate words, and use the cosine similarity to calculate a score for each target word and candidate word pair, the one with a highest score is chosen as the final answer …

A cognitive system for business and technical support: A case study
P Dhoolia, P Chugh, P Costa… – IBM Journal of …, 2017 – ieeexplore.ieee.org
… To extract the question, our domain and cluster- independent strategy is to create a union vector (on the problem description field) for the tickets in the chosen cluster, and then pick the description with the highest cosine similarity with the union vector as the question …

Topic Identification for Speech without ASR
C Liu, J Trmal, M Wiesner, C Harman… – arXiv preprint arXiv …, 2017 – arxiv.org
… For UTD, we use the ZRTools [8] implementation with the default parameters except that, we use cosine similarity thresh- old ? = 0.5, and vary the diagonal … [14] C. Liu, P. Xu, and R. Sarikaya, “Deep contextual language under- standing in spoken dialogue systems.” in Proc …

Learning to attend, copy, and generate for session-based query suggestion
M Dehghani, S Rothe, E Alfonseca, P Fleury – arXiv preprint arXiv …, 2017 – arxiv.org
… is approach prior- itizes words carrying important semantic information over common ones [28]. en, we compute the similarity between the generated query and the target query vectors using the cosine similarity. Retrieval Based ery Similarity …

Question Answering System: A Review On Question Analysis, Document Processing, And Answer Extraction Techniques.
FS UTOMO, N SURYANA… – Journal of Theoretical & …, 2017 – search.ebscohost.com
Page 1. Journal of Theoretical and Applied Information Technology 31st July 2017. Vol.95. No 14 © 2005 – ongoing JATIT & LLS ISSN: 1992-8645 www.jatit.org E-ISSN: 1817-3195 3158 QUESTION ANSWERING SYSTEM : A REVIEW ON …

Speaker and Language Recognition and Characterization: Introduction to the CSL Special Issue
E Lleida, LJ Rodriguez-Fuentes – 2017 – Elsevier
… On the other hand, spoken language recognition (SLR) has also witnessed a remarkable interest from the community as an auxiliary technology for speech recognition (Gonzalez-Dominguez et al., 2015b), dialogue systems (Lopez-Cozar and Araki, 2005) and multimedia …

HMM-based phrase-independent i-vector extractor for text-dependent speaker verification
H Zeinali, H Sameti, L Burget – IEEE/ACM Transactions on …, 2017 – ieeexplore.ieee.org
… To verify speaker identity, the similarity between i-vectors can be mea- sured by simple cosine similarity or using a more elaborate Bayesian model such as Probabilistic Linear Discriminant Anal- ysis (PLDA) [4]–[6]. Fostered primarily by the NIST Speaker Recognition …

Unbounded cache model for online language modeling with open vocabulary
E Grave, MM Cisse, A Joulin – Advances in Neural Information …, 2017 – papers.nips.cc
… One of the most popular strategies is Locality-sensitive hashing (LSH) by Charikar [11], which uses random projections to approximate the cosine similarity between vectors by a function … Building end-to-end dialogue systems using generative hierarchical neural network models …

Recent trends in deep learning based natural language processing
T Young, D Hazarika, S Poria, E Cambria – arXiv preprint arXiv …, 2017 – arxiv.org
… computers to perform a wide range of natural language related tasks at all levels, ranging from parsing and part-of-speech (POS) tagging, to machine translation and dialog systems … Mea- suring similarity between vectors is possible, using measures such as cosine similarity …

Learning to A end, Copy, and Generate for Session-Based ery Suggestion
M Dehghani, S Rothe, E Alfonseca, P Fleury – 2017 – pdfs.semanticscholar.org
… is approach prior- itizes words carrying important semantic information over common ones [28]. en, we compute the similarity between the generated query and the target query vectors using the cosine similarity. Retrieval Based ery Similarity …

Aligning textual and graphical descriptions of processes through ILP techniques
J Sànchez-Ferreres, J Carmona, L Padró – International Conference on …, 2017 – Springer
… determining in which language a text is written, to high-level complex applications such as Machine Translation, Dialogue Systems, or Intelligent … Three similarity metrics are available as parameters: The Cosine similarity and the weighted versions of the Jaccard index and the …

A Sequential Matching Framework for Multi-turn Response Selection in Retrieval-based Chatbots
Y Wu, W Wu, C Xing, C Xu, Z Li, M Zhou – arXiv preprint arXiv:1710.11344, 2017 – arxiv.org
… academia. Existing conversational agents can be categorized into task-oriented dialog systems and non-task-oriented chatbots. Dialog systems focus on helping people complete specific tasks in vertical domains (Young et al …

Automated Crowdturfing Attacks and Defenses in Online Review Systems
Y Yao, B Viswanath, J Cryan, H Zheng… – Proceedings of the 2017 …, 2017 – dl.acm.org
… 3Since Yelp also includes reviews for non-restaurant business, eg, hair salon and car service. cosine similarity between unigram features among all pairs of sentences [10, 20, 31, 56]. • Structural features (4): Captures the structural aspects of a review …

Joint Learning of Response Ranking and Next Utterance Suggestion in Human-Computer Conversation System
R Yan, D Zhao – Proceedings of the 40th International ACM SIGIR …, 2017 – dl.acm.org
Page 1. Joint Learning of Response Ranking and Next Utterance Suggestion in Human-Computer Conversation System Rui Yan †,? 1 Institute of Computer Science and Technology Peking University Beijing 100871, China ruiyan@pku.edu.cn …

Natural language inference over interaction space
Y Gong, H Luo, J Zhang – arXiv preprint arXiv:1709.04348, 2017 – arxiv.org
… machine translation(Bahdanau et al., 2014), abstractive summa- rization(Rush et al., 2015), Reading Comprehension(Hermann et al., 2015), dialog system(Mei et al., 2016 … A common approach is to compute the cosine similarity or dot product between each pair of feature vector …

Computational models for semantic textual similarity
A González Aguirre – 2017 – addi.ehu.es
Page 1. UNIVERSITY OF THE BASQUE COUNTRY Computer Languages and Systems PhD Thesis Computational Models for Semantic Textual Similarity Aitor Gonzalez-Agirre 2017 (c)2017 AITOR GONZALEZ AGIRRE Page 2. Page 3 …

Learning proactive behavior for interactive social robots
P Liu, DF Glas, T Kanda, H Ishiguro – Autonomous Robots, 2017 – Springer
… action using a timing threshold. This assumption has been made in HRI (Thomaz and Chao 2011; Chao and Thomaz 2011) and other spoken dialogue systems as well (Raux and Eske- nazi 2008). To determine a time threshold …

Linguistic Knowledge Transfer for Enriching Vector Representations
JK Kim – 2017 – rave.ohiolink.edu
Page 1. Linguistic Knowledge Transfer for Enriching Vector Representations DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Joo-Kyung Kim, BE, MS …

Information Retrieval Models: Trends and Techniques
S Krishnamurthy, V Akila – Web Semantics for Textual and Visual …, 2017 – igi-global.com
… It is mostly adopted in many systems like library OPAC’s, dialog systems and few search engines. Example … Usually cosine similarity is used to measure the similarity of document and the query vector. Page 11. Information Retrieval Models 27 TF-IDF Weighting Scheme …

Situated Intelligent Interactive Systems
Z Yu – 2017 – lti.cs.cmu.edu
… Abstract The recent wide usage of Interactive Systems (or Dialog Systems), such as Apple’s Siri has at- tracted a lot of attention. Besides personal assistants, dialog systems can also be applied in various domains, such as education, health care and entertainment …

A real-time ensemble classification algorithm for time series data
X Zhu, S Zhao, Y Yang, H Tang… – Agents (ICA), 2017 …, 2017 – ieeexplore.ieee.org
… KNN) algorithm with a number of other similarity measures applied such as Jaccard similarity, Cosine similarity and Euclidean … H. Su, D. Vandyke, and S. Young, Semantically conditioned LSTM-based natural language generation for spoken dialogue systems, arXiv:1508.01745 …

Deriving and Exploiting Situational Information in Speech: Investigations in a Simulated Search and Rescue Scenario
S Mokaram Ghotoorlar – 2017 – etheses.whiterose.ac.uk
… xviii List of Figures 4.1 Visualisation of self-similarity plot for one example Map1 con- versation transcript in the SSAR corpus. Cosine similarity scores every pair of utterances are presented with a gray levels ranging from white for zero (no similarity), to black for one (highly …

Tag Recommendation for Short Arabic Text by Using Latent Semantic Analysis of Wikipedia 
YKA Samra, IM Alagha – 2017 – mobt3ath.com
… This step allows the system to discover hidden semantics between the input short text and the Wikipedia articles by calculating cosine similarity. Tags are selected from the titles … close a document is to a query etc. can be deduced by cosine similarity. However, such …

Integrating both Visual and Audio Cues for Enhanced Video Caption
W Hao, Z Zhang, H Guan, G Zhu – arXiv preprint arXiv:1711.08097, 2017 – arxiv.org
… task which needs long temporal depen- dency, such as visual question answering (Xiong, Merity, and Socher 2016) and dialog systems (Dodge et … the similarity between each element of memory and the key value keys t at time t. Here, we apply cosine similarity metric function …

A Framework For Enhancing Speaker Age And Gender Classification By Using A New Feature Set And Deep Neural Network Architectures
A Abumallouh – 2017 – scholarworks.bridgeport.edu
… SCM SDC Class Models SDS Spoken Dialogue Systems SSM SDC Speaker Models … In [84] a system for detecting the older people over the spoken dialogue systems(SDS) to meet their needs is proposed. Authors in this paper try to distinguish …

Monitoring disaster impact: detecting micro-events and eyewitness reports in mainstream and social media
H Tanev, V Zavarella, J Steinberger – idl.iscram.org
… b. Cluster the terms, using the cosine similarity between their feature vectors … G., Klasinas, I. , Georgiladakis, S., Iosif, E. and Potamianos, A. (2014) Using lexical, syntactic and semantic features for non-terminal grammar rule induction in Spoken Dialogue Systems, IEEE Spoken …

Structured learning for spoken language understanding in human-robot interaction
E Bastianelli, G Castellucci, D Croce… – … Journal of Robotics …, 2017 – journals.sagepub.com
Robots are slowly becoming a part of everyday life, being marketed for commercial applications such as telepresence, cleaning or entertainment. Thus, the abilit…

Learning an Executable Neural Semantic Parser
J Cheng, S Reddy, V Saraswat, M Lapata – arXiv preprint arXiv …, 2017 – arxiv.org
Page 1. arXiv:1711.05066v1 [cs.CL] 14 Nov 2017 Learning an Executable Neural Semantic Parser Jianpeng Cheng University of Edinburgh Siva Reddy Stanford University Vijay Saraswat IBM TJ Watson Research Mirella Lapata University of Edinburgh …

Neural Models for Information Retrieval
B Mitra, N Craswell – arXiv preprint arXiv:1705.01509, 2017 – arxiv.org
Page 1. Neural Models for Information Retrieval Bhaskar Mitra Microsoft, UCL? Cambridge, UK bmitra@microsoft.com Nick Craswell Microsoft Bellevue, USA nickcr@microsoft.com Abstract Neural ranking models for information …

Evaluation of Modern Tools for an OMSCS Advisor Chatbot
E Gregori – 2017 – smartech.gatech.edu
… “?A text based natural language dialogue system specifically developed for the purpose of holding structured, goal directed coaching conversations … The distance between words is than the Euclidian distance or Cosine similarity between vectors …

An interactive interface for nursing robots.
A Sahu – 2017 – ir.library.louisville.edu
Page 1. University of Louisville ThinkIR: The University of Louisville’s Institutional Repository Electronic Theses and Dissertations 8-2017 An interactive interface for nursing robots. Ankita Sahu University of Louisville Follow …

Learning Semantic Patterns for Question Generation and Question Answering
HP Rodrigues – 2017 – pdfs.semanticscholar.org
… This approach of learning by analogy, or example-based systems [Aamodt and Plaza, 1994], has also been applied in other domains, such as in creation of dialog systems [Nio et al., 2014] or translation of unknown words [Langlais and Patry, 2007] …

A joint deep model of entities and documents for cumulative citation recommendation
L Ma, D Song, L Liao, Y Ni – Cluster Computing, 2017 – Springer
Page 1. Cluster Comput DOI 10.1007/s10586-017-1273-x A joint deep model of entities and documents for cumulative citation recommendation Lerong Ma1,2 · Dandan Song1 · Lejian Liao1 · Yao Ni1 Received: 29 June 2017 …

Recommending social platform content using deep learning
J JAXING, A HÅKANSSON, M GORETSKYY… – publications.lib.chalmers.se
Page 1. Recommending social platform content using deep learning A reccurrent neural network model as an alternative to existing recommender systems Bachelor of Science Thesis in Computer Science and Engineering JESPER …

Neural Logic Framework for Digital Assistants
N Cingillioglu, A Russo, K Broda – 2017 – imperial.ac.uk
… 52 4.4 Matching noisy facts to template The capital city is X at k = 0.7. . . . . 55 5.1 Examples of cosine similarity using GloVe [3] vectors. . . . . 65 5.2 Comparison of document average and normalised bag-of-words similarity. . 67 …

Exploring Cells and Context Approaches for RNN Based Conversational Agents
S Johnsrud, S Christensen – 2017 – brage.bibsys.no
… 49 5.1 OOV word replacements using cosine similarity … Our approach suggests using a word represen- tation model to represent all words with word embedding vectors. All OOV words will be replaced with the closest in-vocabulary word, by calculating the cosine similarity …

Helping users learn about social processes while learning from users: developing a positive feedback in social computing
VSS Pillutla – 2017 – search.proquest.com
… edges. Similarity is computed using cosine similarity. Dotted lines denote edges … The similarity between two sentences (ie,. the edges value) is then computed using the cosine similarity, which can be seen as a method of. normalizing the document length during comparison. 20 …

Advances in Neural Networks-ISNN 2017: 14th International Symposium, ISNN 2017, Sapporo, Hakodate, and Muroran, Hokkaido, Japan, June 21–26, 2017 …
F Cong, A Leung, Q Wei – 2017 – books.google.com
Page 1. Fengyu Cong· Andrew Leung Qinglai Wei (Eds.) Advances in Neural Networks – ISNN 2017 14th International Symposium, ISNN 2017 Sapporo, Hakodate, and Muroran, Hokkaido, Japan, June 21–26, 2017 Proceedings, Part I 123 Page 2 …

Comprehensive Medicinal Chemistry III 30010. Fingerprints and other molecular descriptions for database analysis and searching
D Bajusz, A Rácz, K Héberger – researchgate.net
… 2.1.3.2 Representation of Organic Structures Description Arranged Linearly (ROSDAL) The ROSDAL notation was developed in 1985 in the Beilstein Institute and has powered the Beilstein DIALOG system (or Beilstein-Online). 30 It is quite intuitive, but not easily readable …

Deep Reinforcement Learning in Natural Language Scenarios
J He – 2017 – digital.lib.washington.edu
… good/bad endings. Another example is a human-computer dialog system, where the action is the response generated by the dialog manager … computing cosine similarity. Recently, Chen et al. developed a fully discriminative learning …

Heterogeneous resource mobile sensing: computational offloading, scheduling and algorithm optimisation
P Georgiev – 2017 – cl.cam.ac.uk
… audio stream, including: (i) recognise if spoken words are present (and not any other type of sound); (ii) perform spoken keyword spotting (as all commands are begun with the same starting word); and, (iii) speech recognition, along with additional dialogue system analysis that …

Automatic Text Simplification
H Saggion – Synthesis Lectures on Human Language …, 2017 – morganclaypool.com
… Semantic Role Labeling Martha Palmer, Daniel Gildea, and Nianwen Xue 2010 Spoken Dialogue Systems Kristiina Jokinen and Michael McTear 2009 Introduction to Chinese Natural Language Processing Kam-Fai Wong, Wenjie Li, Ruifeng Xu, and Zheng-sheng Zhang 2009 …

Learning Logic Rules From Text Using Statistical Methods For Natural Language Processing
M KAZMI – 2017 – peterschueller.com
Page 1. LEARNING LOGIC RULES FROM TEXT USING STATISTICAL METHODS FOR NATURAL LANGUAGE PROCESSING by MISHAL KAZMI Submitted to the Graduate School of Engineering and Natural Sciences in Partial Fulfillment of the Requirements for the Degree of …

Dissertations in Forestry and Natural Sciences
RG HAUTAMÄKI – epublications.uef.fi
Page 1. Dissertations in Forestry and Natural Sciences D IS S E R T A T IO N S | R O S AG O N Z Á L E ZH A U T A M Ä K I | H U M A N -IN D U C E DV O IC EM O D IF IC A T IO NA N DS P E A K E R … | N o 29 0 ROSA GONZÁLEZ HAUTAMÄKI …

Computational modeling of turn-taking dynamics in spoken conversations
SA Chowdhury – 2017 – eprints-phd.biblio.unitn.it
Page 1. PhD Dissertation International Doctorate School in Information and Communication Technologies DISI – University of Trento COMPUTATIONAL MODELING OF TURN-TAKING DYNAMICS IN SPOKEN CONVERSATIONS Shammur Absar Chowdhury Advisor: Prof …

Data-Driven HRI: Reproducing interactive social behaviors with a conversational robot
CC Liu – 2017 – ir.library.osaka-u.ac.jp
Page 1. Title Data-Driven HRI : Reproducing interactive social behaviors with a conversational robot Author(s) Liu, Chun Chia Citation Issue Date Text Version ETD URL https://doi.org/ 10.18910/61827 DOI 10.18910/61827 rights Page 2. Data-Driven HRI …

Computer Vision and Natural Language Processing: Recent Approaches in Multimedia and Robotics
P Wiriyathammabhum, D Summers-Stay… – ACM Computing …, 2017 – dl.acm.org
Page 1. 71 Computer Vision and Natural Language Processing: Recent Approaches in Multimedia and Robotics PERATHAM WIRIYATHAMMABHUM, University of Maryland, College Park DOUGLAS SUMMERS-STAY, US …

Adjusting linguistically to others: the role of social context In lexical choices and spatial language
A Tosi – 2017 – era.lib.ed.ac.uk
Page 1. This thesis has been submitted in fulfilment of the requirements for a postgraduate degree (eg PhD, MPhil, DClinPsychol) at the University of Edinburgh. Please note the following terms and conditions of use: This work …

Entity-Centric Discourse Analysis and Its Applications
X Wang – 2017 – repository.kulib.kyoto-u.ac.jp
Page 1. Title Entity-Centric Discourse Analysis and Its Applications( Dissertation_ ?? ) Author(s) Wang, Xun Citation Kyoto University (????) Issue Date 2017-11-24 URL https://dx.doi.org/10.14989/doctor.k20777 Right The …

Methods and Techniques for Clinical Text Modeling and Analytics
Y Ling – 2017 – search.proquest.com
Methods and Techniques for Clinical Text Modeling and Analytics. Abstract. This study focuses on developing and applying methods/techniques in different aspects of the system for clinical text understanding, at both corpus and document level …

Modeling common sense knowledge via scripts
A Modi – 2017 – publikationen.sulb.uni-saarland.de
Page 1. Modeling Common Sense Knowledge via Scripts UNIVERSITÄT DES SAARLANDES Ashutosh Modi A dissertation submitted towards the degree Doctor of Engineering of the Faculty of Mathematics and Computer Science of Saarland University Saarbrücken, July 2017 …

(Visited 56 times, 1 visits today)