Machine Learning Approach for Question Answering in Information Retrieval

Authors

  • G. N. Prithy  Department of Computer Science and Engineering, R. M. K Engineering College R. S. M. Nagar, Kavaraipettai, Tamil Nadu, India
  • S. Selvi  Department of Computer Science and Engineering, R. M. K Engineering College R. S. M. Nagar, Kavaraipettai, Tamil Nadu, India

Keywords:

CQA, Natural Language Processing, Mining.

Abstract

CQA (Community Question Answering) is a major challenge nowadays due to the popularity and advantages of CQA archives over the web. This paper deals with the methods to solve lexical gap problem in question retrieval and providing multiple domain based CQA archives. The aim of question answering in CQA is to find the existing questions that are similar to the question being asked but this has become a big challenge due to the lexical gap problem. In this paper, we have proposed to learn the word embedding and the category under which the question is being asked by using natural language processing. Three methods are being used. One is local mining and the other is global mining. In local mining the question s answer is checked in the local database, if found the answer is retrieved back else the global mining process starts in which the answer is checked in other sites information and the relevant answer is retrieved back. Third concept is the expert level where the answer for the query is got from an expert.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2018-02-28

Issue

Volume 3, Issue 1, January-February-2018

Section

Research Articles

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How to Cite

[1]
G. N. Prithy, S. Selvi, " Machine Learning Approach for Question Answering in Information Retrieval, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 1, pp.1549-1556, January-February-2018.