A Review on Deep Learning Techniques Applied to Answer Selection

Given a question and a set of candidate answers, answer selection is the task of identifying which of the candidates answers the question correctly. It is an important problem in natural language processing, with applications in many areas. Recently, many deep learning based methods have been proposed for the task. They produce impressive performance without relying on any feature engineering or expensive external resources. In this paper, we aim to provide a comprehensive review on deep learning methods applied to answer selection.

[1]  Si Li,et al.  A Compare-Aggregate Model with Dynamic-Clip Attention for Answer Selection , 2017, CIKM.

[2]  Tie-Yan Liu,et al.  Learning to rank: from pairwise approach to listwise approach , 2007, ICML '07.

[3]  Yann LeCun,et al.  Signature Verification Using A "Siamese" Time Delay Neural Network , 1993, Int. J. Pattern Recognit. Artif. Intell..

[4]  Siu Cheung Hui,et al.  Hyperbolic Representation Learning for Fast and Efficient Neural Question Answering , 2017, WSDM.

[5]  Christopher D. Manning,et al.  Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks , 2015, ACL.

[6]  Jeffrey Dean,et al.  Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.

[7]  Jian Zhang,et al.  SQuAD: 100,000+ Questions for Machine Comprehension of Text , 2016, EMNLP.

[8]  Bowen Zhou,et al.  LSTM-based Deep Learning Models for non-factoid answer selection , 2015, ArXiv.

[9]  Zhiguo Wang,et al.  Bilateral Multi-Perspective Matching for Natural Language Sentences , 2017, IJCAI.

[10]  Yi Yang,et al.  WikiQA: A Challenge Dataset for Open-Domain Question Answering , 2015, EMNLP.

[11]  Hang Li,et al.  Convolutional Neural Network Architectures for Matching Natural Language Sentences , 2014, NIPS.

[12]  Ming-Wei Chang,et al.  Question Answering Using Enhanced Lexical Semantic Models , 2013, ACL.

[13]  Chris Callison-Burch,et al.  Answer Extraction as Sequence Tagging with Tree Edit Distance , 2013, NAACL.

[14]  Stefan Carlsson,et al.  CNN Features Off-the-Shelf: An Astounding Baseline for Recognition , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops.

[15]  Zhiguo Wang,et al.  Semi-supervised Clustering for Short Text via Deep Representation Learning , 2016, CoNLL.

[16]  Preslav Nakov,et al.  SemEval-2015 Task 3: Answer Selection in Community Question Answering , 2015, *SEMEVAL.

[17]  Shuohang Wang,et al.  A Compare-Aggregate Model for Matching Text Sequences , 2016, ICLR.

[18]  W. Bruce Croft,et al.  aNMM: Ranking Short Answer Texts with Attention-Based Neural Matching Model , 2016, CIKM.

[19]  Jimmy J. Lin,et al.  Exploring the Effectiveness of Convolutional Neural Networks for Answer Selection in End-to-End Question Answering , 2017, ArXiv.

[20]  Noah A. Smith,et al.  What is the Jeopardy Model? A Quasi-Synchronous Grammar for QA , 2007, EMNLP.

[21]  Bowen Zhou,et al.  Applying deep learning to answer selection: A study and an open task , 2015, 2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU).

[22]  Jimmy J. Lin,et al.  Noise-Contrastive Estimation for Answer Selection with Deep Neural Networks , 2016, CIKM.

[23]  Wei Fan,et al.  Reliable Medical Diagnosis from Crowdsourcing: Discover Trustworthy Answers from Non-Experts , 2017, WSDM.

[24]  Jimmy J. Lin,et al.  Multi-Perspective Sentence Similarity Modeling with Convolutional Neural Networks , 2015, EMNLP.

[25]  Noah A. Smith,et al.  Tree Edit Models for Recognizing Textual Entailments, Paraphrases, and Answers to Questions , 2010, NAACL.

[26]  Lei Yu,et al.  Deep Learning for Answer Sentence Selection , 2014, ArXiv.

[27]  James R. Glass,et al.  Supervised and Unsupervised Transfer Learning for Question Answering , 2017, NAACL.

[28]  Yoshua Bengio,et al.  Neural Machine Translation by Jointly Learning to Align and Translate , 2014, ICLR.

[29]  Jonas Mueller,et al.  Siamese Recurrent Architectures for Learning Sentence Similarity , 2016, AAAI.

[30]  Jimmy J. Lin,et al.  Pairwise Word Interaction Modeling with Deep Neural Networks for Semantic Similarity Measurement , 2016, NAACL.

[31]  Tie-Yan Liu,et al.  Learning to rank for information retrieval , 2009, SIGIR.

[32]  Alessandro Moschitti,et al.  Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks , 2015, SIGIR.

[33]  Yoon Kim,et al.  Convolutional Neural Networks for Sentence Classification , 2014, EMNLP.

[34]  Jürgen Schmidhuber,et al.  Long Short-Term Memory , 1997, Neural Computation.

[35]  Jeffrey Pennington,et al.  GloVe: Global Vectors for Word Representation , 2014, EMNLP.

[36]  David A. Ferrucci,et al.  Introduction to "This is Watson" , 2012, IBM J. Res. Dev..

[37]  Yifan Gong,et al.  Cross-language knowledge transfer using multilingual deep neural network with shared hidden layers , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

[38]  Fenglong Ma,et al.  TextTruth: An Unsupervised Approach to Discover Trustworthy Information from Multi-Sourced Text Data , 2018, KDD.

[39]  Zhi-Hong Deng,et al.  Inter-Weighted Alignment Network for Sentence Pair Modeling , 2017, EMNLP.

[40]  Erik Cambria,et al.  Recent Trends in Deep Learning Based Natural Language Processing , 2017, IEEE Comput. Intell. Mag..

[41]  Zhiguo Wang,et al.  Sentence Similarity Learning by Lexical Decomposition and Composition , 2016, COLING.

[42]  Christopher D. Manning,et al.  Effective Approaches to Attention-based Neural Machine Translation , 2015, EMNLP.

[43]  Preslav Nakov,et al.  SemEval-2016 Task 3: Community Question Answering , 2019, *SEMEVAL.

[44]  Tuan Lai,et al.  A Simple End-to-End Question Answering Model for Product Information , 2018, ECONLP@ACL.

[45]  Regina Barzilay,et al.  Aspect-augmented Adversarial Networks for Domain Adaptation , 2017, TACL.

[46]  Mark Andrew Greenwood,et al.  Open-domain question answering , 2005 .

[47]  Ingrid Zukerman,et al.  The Context-Dependent Additive Recurrent Neural Net , 2018, NAACL.

[48]  Siu Cheung Hui,et al.  Multi-Cast Attention Networks , 2018, KDD.

[49]  Christopher Potts,et al.  A large annotated corpus for learning natural language inference , 2015, EMNLP.

[50]  Qiang Yang,et al.  A Survey on Transfer Learning , 2010, IEEE Transactions on Knowledge and Data Engineering.

[51]  Hannaneh Hajishirzi,et al.  Question Answering through Transfer Learning from Large Fine-grained Supervision Data , 2017, ACL.

[52]  Holger Schwenk,et al.  Supervised Learning of Universal Sentence Representations from Natural Language Inference Data , 2017, EMNLP.

[53]  Phil Blunsom,et al.  Teaching Machines to Read and Comprehend , 2015, NIPS.

[54]  Christopher D. Manning,et al.  Probabilistic Tree-Edit Models with Structured Latent Variables for Textual Entailment and Question Answering , 2010, COLING.

[55]  Phil Blunsom,et al.  A Convolutional Neural Network for Modelling Sentences , 2014, ACL.