[PDF] Top 20 Improved Representation Learning for Question Answer Matching
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Improved Representation Learning for Question Answer Matching
... While this task is usually approached as a pairwise-ranking problem, the best strategy to cap- ture the association between the questions and an- swers is still an open problem. Established ap- proaches normally suffer ... See full document
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On Committee Representations of Adversarial Learning Models for Question Answer Ranking
... Deep Matching Network and its ...Deep Matching Net- work on some of the ...adversarial learning provides a significant boost in model per- formance for Match Pyramid and Deep Match- ing Network, the ... See full document
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Representation Learning for Answer Selection with LSTM Based Importance Weighting
... InsuranceQA v1 Our evaluation on InsuranceQA v1 allows us to compare our approach against a broad list of recently published attention-based models. Table 2 shows the results of our evaluation where we measure the ratio ... See full document
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Learning Question Guided Video Representation for Multi Turn Video Question Answering
... Video question answering is a specific scenario of such AI-human interaction where an agent generates a natural language response to a question regarding the video of a dynamic ...video question ... See full document
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Adversarial Training for Community Question Answer Selection Based on Multi-Scale Matching
... significantly improved and outperform pre- vious methods which are primarily based on feature engi- neering (Filice, Da Martino, and Moschitti 2017; Xie et ...each question is as- sociated with 100 ... See full document
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Active Reading Comprehension: A Dataset for Learning the Question Answer Relationship Strategy
... the question with the words in the ...beyond matching ability; the reader should be able to conclude that the information in sentences 6 and 7 are equally re- quired to answer the question ... See full document
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Learning Unsupervised SVM Classifier for Answer Selection in Web Question Answering
... for answer selec- tion that is validated in Chinese open-domain web ...Regarding answer selection as a kind of classifi- cation task, the U-SVM automatically learns clusters and pseudo-training data for ... See full document
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FreebaseQA: A New Factoid QA Data Set Matching Trivia Style Question Answer Pairs with Freebase
... can retrieve information. Knowledge graphs are colossal networks of data that describe concepts, entities, and their relations. In fact, Freebase is the largest publicly-available knowledge graph, con- sisting of 4 ... See full document
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Learning Strategies for Open Domain Natural Language Question Answering
... approach, matching the question with the lexically most similar sentence in the ...the answer based on a combination of syntactic similarity and semantic correspondence ...bag-of-verb ... See full document
6
Open Domain Why Question Answering with Adversarial Learning to Encode Answer Texts
... why- question answering (why-QA) that uses an ad- versarial learning ...retrieve answer passages that usually consist of several ...compact-answer Representation (AGR) to generate from ... See full document
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DeepCF: A Unified Framework of Representation Learning and Matching Function Learning in Recommender System
... common representation space where they can be com- pared ...deep learning methods have shown promising results in various areas such as computer vision, speech recognition and natural language ...item ... See full document
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Learning When Not to Answer: a Ternary Reward Structure for Reinforcement Learning Based Question Answering
... User-facing question answering systems inher- ently face a trade-off between presenting an an- swer to a user that could potentially be incorrect, and choosing not to ...graph question-answering (QA) only ... See full document
8
Gated Self Matching Networks for Reading Comprehension and Question Answering
... self- matching networks for reading compre- hension style question answering, which aims to answer questions from a given pas- ...the question and pas- sage with gated attention-based ... See full document
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Answer Sequence Learning with Neural Networks for Answer Selection in Community Question Answering
... on answer selection generally treat- ed this challenge as a classification problem via employing machine learning methods, which re- ly on exploring various features to represent QA ...the answer ... See full document
6
A Factoid Question Answering System Using Answer Pattern Matching
... the question phrase and the answer phrase in the retrieved ...our answer patterns have almost twice the chance to extract answers using query ...our answer patterns in our best combination ... See full document
5
Stack propagation: Improved Representation Learning for Syntax
... Traditional syntax models typically lever- age part-of-speech (POS) information by constructing features from hand-tuned templates. We demonstrate that a better approach is to utilize POS tags as a reg- ularizer of ... See full document
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This is how we do it: Answer Reranking for Open domain How Questions with Paragraph Vectors and Minimal Feature Engineering
... Even our best model is still, however, far from be- ing perfect, i.e. for about 60% of questions, the an- swer selected as best by the author of the question is not assigned the highest rank by our system. We be- ... See full document
6
If technology is the answer, what is the question?
... Digital Pedagogy is precisely not about using digital technologies for teaching and, rather, about approaching those tools from a critical pedagogical perspective.. So, it is as much abo[r] ... See full document
84
A. Question Clustering and Answer Prediction
... Second, question clustering and answer prediction functionalities were appreciated by most ...to question clustering, participant 8 felt that retrieving answers would be easier as “the same ... See full document
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MixKMeans: Clustering Question Answer Archives
... Future Work: As discussed in Section 4.4, MixKMeans is eminently generalizable to beyond two spaces. Considering the usage of other kinds of data (e.g., tags, comments) as additional “spaces” to extend the CQA clustering ... See full document
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