[PDF] Top 20 Neural Generative Question Answering
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Neural Generative Question Answering
... the question, is retrieved by using the Aho-Corasick string searching ...of question, answer, triple) are finally obtained with an estimated 80% of instances being truly ... See full document
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EviNets: Neural Networks for Combining Evidence Signals for Factoid Question Answering
... given question, we ex- tract potentially relevant information, ...Finally, question, answer candidates and support- ing evidence are given as input to the EviNets neu- ral ... See full document
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Question Answering over Freebase with Multi Column Convolutional Neural Networks
... conduct question under- standing and/or answer ...tional neural networks (MCCNNs) to un- derstand questions from three different as- pects (namely, answer path, answer con- text, and answer type) and learn ... See full document
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Learning Semantic Relatedness in Community Question Answering Using Neural Models
... a neural-based model with stacked bidirectional LSTMs to generate the vector representations of questions and answers, and predict their semantic ...the question retrieval task, and a list of answers in the ... See full document
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Uncovering Code Mixed Challenges: A Framework for Linguistically Driven Question Generation and Neural Based Question Answering
... 2017), question clas- sification (Raghavi et ...of question generation (general) include both rules Heilman and Smith (2010); Ali et ...and answering based on sequence- to-sequence neural ... See full document
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Question Generation for Question Answering
... using neural networks, where large scale QA pairs are automatically crawled and processed from Community-QA website, and used as training ...of question generation approaches are proposed, one is a ... See full document
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Search based Neural Structured Learning for Sequential Question Answering
... the question “Which super heroes came from Earth and first appeared after 2009?” is “Se- lect Character Where {Home World = Earth } ∧ {First Appeared > 2009}” and the answers are {Dragonwing, ... See full document
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Improved Neural Relation Detection for Knowledge Base Question Answering
... Analysis Next, we present empirical evidences, which show why our HR-BiLSTM model achieves the best scores. We use WebQSP for the analy- sis purposes. First, we have the hypothesis that training of the weighted-sum model ... See full document
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Applying deep matching networks to Chinese medical question answering: a study and a dataset
... TextRank [15] algorithm to the re-ranking of candidates. His data were crawled from the web and not publicly available. The method was based on words and suffered from Chinese word segmentation failure in some cases. ... See full document
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Answer Sequence Learning with Neural Networks for Answer Selection in Community Question Answering
... It is clear to see that the proposed R-CNN ap- proach outperforms the competitor methods over the Macro-averaged metrics as expected from Ta- ble 2. The main reason lies in that R-CNN takes advantages of the semantic ... See full document
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Question Answering in the Biomedical Domain
... Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, Jeff Klingner, Apurva Shah, Melvin Johnson, Xiaob- ing Liu, Lukasz Kaiser, Stephan ... See full document
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Learning to Paraphrase for Question Answering
... to question an- ...of neural question answering models (Bordes et ...on question-answer pairs, and em- ploy question paraphrases in a multi-task learning framework in an attempt ... See full document
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Evaluating Question Answering Evaluation
... of question answering (QA) datasets evolve, moving away from restricted formats like span extraction and multiple- choice (MC) to free-form answer generation, it is imperative to understand how well current ... See full document
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Routing Questions for Collaborative Answering in Community Question Answering
... the question answering as an information retrieval process with the purpose of satisfying the question ...of question asker and found information seeking patterns that correlate with ...the ... See full document
8
Neural Attention for Learning to Rank Questions in Community Question Answering
... of neural models for answer selec- tion (Severyn and Moschitti, 2015; Tan et ...and question similarity (dos Santos et ...a neural attention model for machine trans- lation and showed that the ... See full document
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CFO: Conditional Focused Neural Question Answering with Large scale Knowledge Bases
... As discussed in section 3.2, N-Gram pruning is still subject to large amount of noise in inference due to many non-subject-mention n-grams. Moti- vated by this problem, we propose to reduce such noise by focusing on more ... See full document
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Enhancing Key Value Memory Neural Networks for Knowledge Based Question Answering
... to compose the key-value memory. Particularly, one can first detect entity mentions in the ques- tion, and include all KB facts that contains with one of those entities as subject into the memory. In our experiments, we ... See full document
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Learning to Compose Neural Networks for Question Answering
... Neural models for question answering are also a subject of current interest. These include ap- proaches that model the task directly as a multiclass classification problem (Iyyer et al., 2014), ... See full document
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A Neural Network for Factoid Question Answering over Paragraphs
... training question text for that answer. Given a partial question, the text is first preprocessed using a query lan- guage similar to that of Apache ...the question text, this is not a valid ... See full document
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Neural Arabic Question Answering
... Open-domain Arabic question answering. The state of current Arabic QA systems is summarized in (Shaheen and Ezzeldin, 2014): research has focused mostly on open-ended QA using classi- cal information ... See full document
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