Keywords based Closed Domain Question Answering System for Indian Penal Code Sections and Indian Amendment Laws

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Author(s)

Rohini P. Kamdi 1,* Avinash J. Agrawal 2

1. SRCOEM, M.Tech, Computer Science Engineering, Nagpur, India

2. SRCOEM, Associate Professor, Computer Science Engineering, Nagpur, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijisa.2015.12.06

Received: 5 Apr. 2015 / Revised: 5 Aug. 2015 / Accepted: 20 Sep. 2015 / Published: 8 Nov. 2015

Index Terms

Question Answering, Information Retrieval Natural language processing, Indian Penal Code (IPC) sections, Indian Amendment laws, keywords and knowledge-base

Abstract

In information retrieval, Question Answering (QA) is the task of answering a question posed in natural language (NL) using either a pre-structured database or a collection of natural language documents without human intervention. Question Answering systems are categorized on their available resource for answers. The domain specific Question Answering System gives more exact and correct answers than web based Question Answering system as it is limited for only one domain resource to answer. This paper proposes the closed domain Question Answering System for handling the legal documents of Indian Penal Code (IPC) sections and Indian Amendment Laws to retrieve more precise answers. This system tries to retrieve the exact answers from stored knowledge-base for the query related to Indian Penal Code (IPC) sections and Indian Amendment Laws asked by user. This Keyword based Question Answering System works on structured, unstructured and non-question form queries. The closed domain Question Answering system gives more accurate answer than other open domain system as it restricted single resource. Keywords from both queries and answer corpus play important role for extracting answer.

Cite This Paper

Rohini P. Kamdi, Avinash J. Agrawal, "Keywords based Closed Domain Question Answering System for Indian Penal Code Sections and Indian Amendment Laws", International Journal of Intelligent Systems and Applications(IJISA), vol.7, no.12, pp.57-67, 2015. DOI:10.5815/ijisa.2015.12.06

Reference

[1]Pum-Mo Ryu, Myung-Gil Jang and Hyun-Ki Kim. 2014. “Open domain question answering using Wikipedia-based knowledge model.” In Information Processing and Management 50 (2014) 683–692, Elsevier.
[2]Adel Tahri and Okba Tibermacine. “DBPEDIA BASED FACTOID QUESTION ANSWERING SYSTEM.” In International Journal of Web & Semantic Technology (IJWesT) Vol.4, No.3, July 2013.
[3]Pragisha K. and Dr. P. C. Reghuraj, “A Natural Language Question Answering System in Malayalam Using Domain Dependent Document Collection as Repository.” International Journal of Computational Linguistics and Natural Language Processing Vol 3 Issue 3 March 2014 ISSN 2279 – 0756.
[4]Jibin Fu, Keliang Jia and Jinzhong Xu, “Domain Ontology Based Automatic Question Answering”, 2009 International Conference on Computer Engineering and Technology.
[5]Anette Frank , Hans-Ulrich Krieger, Feiyu Xu, Hans Uszkoreit, Berthold Crysmann, Brigitte J?rg and Ulrich Sch?fer, “Question answering from structured knowledge sources”, In German Research Center for Artificial Intelligence, DFKI, Stuhlsatzenhausweg 3, 66123 Saarbrücken, Germany Available online 27 January 2006.
[6]Perera, Rivindu (2012) “IPedagogy: Question Answering System Based on Web Information Clustering”, In Proceedings of the 2012 IEEE Fourth International Conference on Technology for Education (T4E '12). IEEE Computer Society, Washington, DC, USA.
[7]Menaka S and Radha N. “Text Classification using Keyword Extraction Technique”, in International Journal of Advanced Research in Computer Science and Software Engineering, Volume 3, Issue 12, December 2013.
[8]MatthewW. Bilotti and Eric Nyberg,” Improving Text Retrieval Precision and Answer Accuracy in Question Answering Systems”, the 2nd workshop on Information Retrieval for Question Answering (IR4QA), pages 1–8 Manchester, UK. August 2008.
[9]Abdullah M. Moussa and Rehab F. Abdel-Kader, QASYO: “A Question Answering System for YAGO Ontology”, International Journal of Database Theory and Application Vol. 4, No. 2, June, 2011.
[10]Eric Brill, Susan Dumais and Michele Banko, “An Analysis of the AskMSR Question-Answering System”, Conference on Empirical Methods in Natural Language Processing (EMNLP), Philadelphia, July 2002, pp. 257-264. Association for Computational Linguistics.
[11]Yaoyong Li, Kalina Bontcheva, and Hamish Cunningham, “SVM Based Learning System For Information Extraction”, Department of Computer Science, The University of She_eld, She_eld, S1 4DP, UK.
[12]Moussa, Abdullah M. & Rehab, Abdel-Kader (2011) “QASYO: A Question Answering System for YAGO Ontology”. International Journal of Database Theory and Application. Vol. 4, No. 2, June, 2011. 99.
[13]W.A.Woods, R.M. Kaplan, B.L. Nash-Webber, “The Lunar sciences natural language information system: Final report”, Technical Report BBN Report 2378, Bolt Beranek and Newman Inc., Cambridge, MA, 1972.
[14]Lee, C., Hwang, Y.-G., Oh, H.J., Lim, S., Heo, J., Lee, C.-H., et al (2006). “Fine-grained named entity recognition using conditional random fields for question answering”. In Proceedings of Asia information retrieval symposium (pp. 581–587).
[15]ZHANG Yu, LIU Ting, WEN Xu, "Modified Bayesian Model Based Question Classificatio", 2005, vol.19, pp. 100-105.
[16]Amit Mishra, Nidhi Mishra and Anupam Agrawal, “Context-Aware Restricted Geographical Domain Question Answering System”, In 2010 International Conference on Computational Intelligence and Communication Networks.
[17]Rohini P. Kamdi and Dr, A. J .Agrawal, “Domain Specific Question Answering System”, in International Journal of Electrical, Electronics And Computer Systems (IJEECS), Vol 4, Issue-2, 2015.
[18]Rohini P. Kamdi and Dr, A. J .Agrawal, “Closed Domain Question Answering System for IPC Sections and Amendment Laws” in The International Journal For Engineering Applications and Technology (IJFEAT),Volume-2, Issue-1, 2015.