[PDF] Top 20 Supervised attention for answer selection in community question answering
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Supervised attention for answer selection in community question answering
... when supervised attention is put into this model, the performance increases steadily as well on both SemevalCQA2016 and ...that supervised attention can learn semantic of question and ... See full document
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Question Condensing Networks for Answer Selection in Community Question Answering
... Answer selection is an important subtask of community question answering ...a question is often represented as two parts: a sub- ject that summarizes the main points of the ... See full document
10
Answer Sequence Learning with Neural Networks for Answer Selection in Community Question Answering
... Answer selection in community question answer- ing (CQA), which recognizes high-quality re- sponses to obtain useful question-answer pairs, is greatly valuable for ... See full document
6
Answer Selection in Arabic Community Question Answering: A Feature Rich Approach
... of answer selection in community ques- tion answering consists of identifying pertinent answers from a pool of user-generated comments related to a ...on community ques- tion ... See full document
8
Dynamic and Multi Match Answer Selection Model for Automobile Question Answering
... a question-answer selection model based on multi-layer convolution neural network, which consists of Embedding layer, convolution layer, pooling layer and similarity calculation ...from ... See full document
7
Supervised and Unsupervised Transfer Learning for Question Answering
... word-level attention map during training Epoch 1, 4, 7, and 10 in Figure ...same question from TOEFL-manual as shown in Table 1 as an ...the question and the correct an- swer choice. For example, the ... See full document
10
Sequential Attention with Keyword Mask Model for Community based Question Answering
... Experiment Results The results are shown in Table 2. Firstly, it is observed that deep neu- ral network models outperform traditional models. Most latent representation models obtain better re- sults than interaction ... See full document
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Adversarial Training for Community Question Answer Selection Based on Multi-Scale Matching
... Community-based question answering (CQA) websites rep- resent an important source of information. As a result, the problem of matching the most valuable answers to their corresponding questions has ... See full document
8
Addressing Semantic Drift in Question Generation for Semi Supervised Question Answering
... claimed none of them improved the quality of gen- erated questions. For QG evaluation, even though some previous works conducted human evalua- tions, most of them still relied on traditional met- rics (e.g., BLEU). ... See full document
15
RelTextRank: An Open Source Framework for Building Relational Syntactic Semantic Text Pair Representations
... e.g., answer sentence selection (AS) and community question answering (cQA), has stud- ied a number of structures for representing text pairs along with their relational links, which ... See full document
6
Neural Attention for Learning to Rank Questions in Community Question Answering
... for answer selec- tion (Severyn and Moschitti, 2015; Tan et ...and question similarity (dos Santos et al., 2015) in community question ...neural attention model for machine trans- ... See full document
12
Learning Unsupervised SVM Classifier for Answer Selection in Web Question Answering
... for answer selection in question answering (QA) have required question-answer train- ing ...for answer selection, which is independent of language and does not re- ... See full document
9
Multi-Task Learning with Multi-View Attention for Answer Selection and Knowledge Base Question Answering
... Answer selection and knowledge base question answering (KBQA) are two important tasks of question answering (QA) ...tackle answer selection and KBQA tasks ... See full document
8
Denoising Distantly Supervised Open Domain Question Answering
... the question “Which country’s capital is Dublin?”, we may encounter that: (1) The retrieved paragraph “Dublin is the largest city of Ireland ...actually answer the question; (2) The second “Dublin” ... See full document
10
Simple and Effective Semi Supervised Question Answering
... Pre-training: We make use of the generated cloze dataset to pre-train an expressive neural net- work designed for the task of reading comprehen- sion. We work with two publicly available neural network models – the GA ... See full document
6
A Graph based Semi Supervised Learning for Question Answering
... the question-answering (QA) task for ranking candidate ...guage question posed by the user and the candidate sentences returned from search ...matching, question-type named-entity matching ... See full document
9
Dynamic Capsule Attention for Visual Question Answering
... The attention dimension in CapsAtt is set to 512, and the ones of the two FC layers are both 512 as ...of answer category is set to ...The answer dimensions on these two datasets are both set to ... See full document
8
Language independent Probabilistic Answer Ranking for Question Answering
... all answer ranking features improved per- formance by an average of 102% over the ...that answer relevance features had a greater impact for English QA because the quality and coverage of the data re- ... See full document
8
RankQA: Neural Question Answering with Answer Re Ranking
... In order to demonstrate the robustness of an- swer re-ranking across different implementations, we repeat experiments from above based on the BERT-QA system. The results are shown in Tbl. 3. The first row displays the ... See full document
10
A Nil Aware Answer Extraction Framework for Question Answering
... the answer sentence selection task, the answer is always a full ...a question, a system needs to find the exact answer span rather than a ...valid answer for a given ...nil-aware ... See full document
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