A Survey on Question –Answering System

Question-Answering(QA) is a new research area/ region in the field of Information science which comes into focus in last few decade. The present study is undertaken to survey about the QA system.The study in this paper will provide the guidelines to the researchers, scholars and practitioners of computer engineering. In this paper, the study is undertaken by planning, conducting, evaluating and reporting the literature review from the past years. A Question –Answering system consists of three core components i.e. question classification ,information retrieval and answer extraction module. This paper aims at giving an overview in this field, evaluating the current and emerging status and visualizing the future scope and trends. KeywordsQuestion –Answering system, text mining, Information Retrieval(IR)

[1]  Michael C. McCord,et al.  Deep parsing in Watson , 2012, IBM J. Res. Dev..

[2]  Walter Daelemans,et al.  Pattern for Python , 2012, J. Mach. Learn. Res..

[3]  James Fan,et al.  Textual evidence gathering and analysis , 2012, IBM J. Res. Dev..

[4]  Jimmy J. Lin,et al.  Overview of the TREC 2007 Question Answering Track , 2008, TREC.

[5]  Oanh Thi Tran,et al.  An Experimental Study of Vietnamese Question Answering System , 2009, 2009 International Conference on Asian Language Processing.

[6]  Jennifer Chu-Carroll,et al.  Special Questions and techniques , 2012, IBM J. Res. Dev..

[7]  Siddharth Patwardhan,et al.  Fact-based question decomposition in DeepQA , 2012, IBM J. Res. Dev..

[8]  William Stafford Noble,et al.  Support vector machine , 2013 .

[9]  Siddharth Patwardhan,et al.  Question analysis: How Watson reads a clue , 2012, IBM J. Res. Dev..

[10]  Alexander H. Waibel,et al.  A Pattern Learning Approach to Question Answering Within the Ephyra Framework , 2006, TSD.

[11]  Yue-Shi Lee,et al.  A support vector machine-based context-ranking model for question answering , 2013, Inf. Sci..

[12]  Boris Katz,et al.  Natural Language Annotations for Question Answering , 2006, FLAIRS Conference.

[13]  Alessandro Moschitti,et al.  Making Tree Kernels Practical for Natural Language Learning , 2006, EACL.

[14]  Dell Zhang,et al.  A Web-based Question Answering System , 2003 .

[15]  Jennifer Chu-Carroll,et al.  Identifying implicit relationships , 2012, IBM J. Res. Dev..

[16]  Bert F. Green,et al.  Baseball: an automatic question-answerer , 1899, IRE-AIEE-ACM '61 (Western).

[17]  Shan Suthaharan,et al.  Support Vector Machine , 2016 .

[18]  Alessandro Moschitti,et al.  Efficient Convolution Kernels for Dependency and Constituent Syntactic Trees , 2006, ECML.

[19]  Wendy G. Lehnert,et al.  A survey of question answering in natural language processing , 1990 .

[20]  Jennifer Chu-Carroll,et al.  Textual resource acquisition and engineering , 2012, IBM J. Res. Dev..

[21]  Roger Levy,et al.  Tregex and Tsurgeon: tools for querying and manipulating tree data structures , 2006, LREC.

[22]  George A. Miller,et al.  WordNet: A Lexical Database for English , 1995, HLT.

[23]  Jennifer Chu-Carroll,et al.  Finding needles in the haystack: Search and candidate generation , 2012, IBM J. Res. Dev..

[24]  Bagde Sneha,et al.  Comparison of Different Similarity Functions on Hindi QA System , 2016 .

[25]  Sanda M. Harabagiu,et al.  Advances in Open Domain Question Answering , 2007 .

[26]  Mai-Vu Tran,et al.  A Model of Vietnamese Person Named Entity Question Answering System , 2012, PACLIC.

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

[28]  Aditya Kalyanpur,et al.  A framework for merging and ranking of answers in DeepQA , 2012, IBM J. Res. Dev..

[29]  Christopher D. Manning,et al.  Incorporating Non-local Information into Information Extraction Systems by Gibbs Sampling , 2005, ACL.

[30]  Zengchang Qin,et al.  Question Classification using Head Words and their Hypernyms , 2008, EMNLP.

[31]  Steven Bird,et al.  NLTK: The Natural Language Toolkit , 2002, ACL.

[32]  Huong Thanh Le,et al.  Natural Language Interface Construction Using Semantic Grammars , 2008, PRICAI.

[33]  Eduard H. Hovy,et al.  The Use of External Knowledge of Factoid QA , 2001, TREC.

[34]  John B. Lowe,et al.  The Berkeley FrameNet Project , 1998, ACL.

[35]  James R. Curran.  Proceedings of the COLING/ACL on Interactive presentation sessions , 2006 .

[36]  Thorsten Joachims,et al.  Making large scale SVM learning practical , 1998 .

[37]  Sanda M. Harabagiu,et al.  Experiments with Open-Domain Textual Question Answering , 2000, COLING.

[38]  Dell Zhang,et al.  Question classification using support vector machines , 2003, SIGIR.

[39]  Tat-Seng Chua,et al.  Discovering high quality answers in community question answering archives using a hierarchy of classifiers , 2014, Inf. Sci..

[40]  Eric W. Brown,et al.  Making Watson fast , 2012, IBM J. Res. Dev..

[41]  B. Bloom.  Taxonomy of educational objectives , 1956 .

[42]  Christopher D. Manning,et al.  Generating Typed Dependency Parses from Phrase Structure Parses , 2006, LREC.

[43]  Chang Wang,et al.  Relation extraction and scoring in DeepQA , 2012, IBM J. Res. Dev..

[44]  Burn L. Lewis.  In the game: The interface between Watson and Jeopardy! , 2012, IBM J. Res. Dev..

[45]  Ralph Grishman,et al.  Hindi-english cross-lingual question-answering system , 2003, TALIP.

[46]  Aditya Kalyanpur,et al.  Typing candidate answers using type coercion , 2012, IBM J. Res. Dev..

[47]  Fuchun Peng,et al.  Combining Deep Linguistics Analysis and Surface Pattern Learning: A Hybrid Approach to Chinese Definitional Question Answering , 2005, HLT.

[48]  Soumen Chakrabarti,et al.  Enhanced Answer Type Inference from Questions using Sequential Models , 2005, HLT/EMNLP.

[49]  Estevam R. Hruschka,et al.  Toward an Architecture for Never-Ending Language Learning , 2010, AAAI.

[50]  Mitsuru Ishizuka,et al.  Relation Extraction from Wikipedia Using Subtree Mining , 2007, AAAI.

[51]  Aditya Kalyanpur,et al.  Automatic knowledge extraction from documents , 2012, IBM J. Res. Dev..

[52]  Dan Roth,et al.  Learning Question Classifiers , 2002, COLING.

[53]  Siddharth Patwardhan,et al.  Structured data and inference in DeepQA , 2012, IBM J. Res. Dev..