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Design of the Effective Question Answering System by Performing Question Analysis using the Classifier
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 139 - Number 14 |
| Year of Publication: 2016 |
| Authors: Gayatri Chavan, Sonal Gore |
10.5120/ijca2016908801
|
Gayatri Chavan, Sonal Gore . Design of the Effective Question Answering System by Performing Question Analysis using the Classifier. International Journal of Computer Applications. 139, 14 ( April 2016), 1-3. DOI=10.5120/ijca2016908801
Abstract
Search engines have played a very important role in helping the users to search the necessary information from the huge information. By displaying the list of links to documents.The Question-Answering systems are gaining popularity. Because The main benefit of such QA systems is that the user can ask the query (question) in natural language and he /she get a precise and appropriate answer instead of just displaying a list of links to documents. The main advantage of the proposed Question answering system, which is not restricted to a specific domain. This approach is related to a natural language interface to the database (NLIDB), which takes a natural language query as input and giving the appropriate answer from the manually created knowledge base(structured database). There are two main steps of implementation of the proposed question answering system. The first step is to use a classifier to identify appropriate tables and columns in a structured database for an incoming question, and the second step is to perform the free text retrieval to lookup answer. The system uses named entity normalization, part-of-speech tagging, and a statistical classifier trained on data from the TREC QA task.
References
- Mahboob Alam Khalid, Valentin Jijkoun, Maarten de Rijke, “Machine Learning for Question Answering from Tabular Data”, 18th International Workshop on Database and Expert Systems Applications, 2007 IEEE.
- Ms. Pooja P. Walke, Mr. Shivkumar Karale, “Implementation Approaches for Various Categories of Question Answering System”, Proceedings of 2013 IEEE Conference on Information and Communication Technologies (ICT 2013), 2013 IEEE.
- Rana Forsati, Mehrnoush Shamsfard, Pouyan Mojtahedpour, “An Efficient Meta Heuristic Algorithm for POS-Tagging”, 2010 Fifth International Multi-conference on Computing in the Global Information Technology, 2010 IEEE.
- Varsha Bhoir, M. A. Potey, “Question Answering System : A Heuristic Approach”, 978-1-4799-2259-14/$31.00©2014.
- Muthukrsihanan Ramprasath and Shanmugasundaram Hariharan, “Improving QA performance through semantic reformulation”, 2012 Nirma University International Conference on Engineering, NUiCONE-2012, 06-08DECEMBER, 2012 IEEE.
- V. Jijkoun, M. de Rijke, and J. Mur. Information extraction for question answering: Improving recall through syntactic patterns. In Proc. COLING 2004, 2004.
- T. Brants. TnT – A Statistical Part-Of-Speech tagger. In Proc. of the 6th Applied NLP Conference, 2000.
- D. Ahn, V. Jijkoun, K. M¨uller, M. de Rijke, and E. Tjong Kim Sang. Towards an offline XML-based strategy for answering questions. In Accessing Multilingual Information Repositories, pages 449–456, 2006.
- M. Fleischman, E. Hovy, and A. Echihabi. Offline strategies for online question answering: answering questions before they are asked. In Proc. ACL ’03, pages 1–7, 2003.
- D. Harman. Overview of the TREC 2002 novelty track. In Proc. TREC 2002, pages 17–28, 2002.
- D. Hiemstra. A linguistically motivated probabilistic model of information retrieval. In Proc. ECDL 1998, pages 569–584, 1998.
- E. Voorhees and D. Tice. The TREC-8 question answering track evaluation. In Proc. TREC-8, 1999.
- G. Ramakrishnan, S. Chakrabarti, D. Paranjpe, and P. Bhattacharyya.Is question answering an acquired skill? In Proc.WWW, pages 111–120, 2004.
- D. Metzler and W. Croft. Analysis of statistical question classification for fact-based questions. Journal of Information Retrieval, 8:481–504, 2005.
- X. Li and D. Roth. Learning question classifiers. In Proc. COLING 2002, 2002.
- J. Allan, C. Wade, and A. Bolivar. Retrieval and novelty detection at the sentence level. In Proc. SIGIR 2003, pages 314–321, 2003
- D. Harman. Overview of the TREC 2002 novelty track. In Proc. TREC 2002, pages 17–28, 2002
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