International Journal of System & Software Engineering

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Improving the Performance of RDQA Using Lexical Based Inference Extraction


Affiliations
1 Computer Science and Engineering Department, Anand institute of Higher Technology, Chennai, Tamil Nadu, India
     

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This paper presents an enhanced approach for Question Classification and Answer Extraction in Restricted Domain Question Answering (RDQA). Question Classification and Answer Extraction is the core problem of RDQA and determines the performance of the Question Answering in the Restricted Domain. The proposed approach improves the performance of RDQA by means of (1) Question type prediction model based on Bayesian classification (2) Lexicalized-Index based Passage Retrieval (3) Lexical-Semantic based Inference Extraction. This paper also describes usercentered task-based evaluations for Answer Validation. Further improvements are achieved by combining our model with the classic one to improve the performance of Restricted Domain Question Answering.

Keywords

Restricted Domain Question Answering (RDQA), Bayesian Classification, Passage Retrieval, Answer Extraction, Text Inference.
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Abstract Views: 331

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  • Improving the Performance of RDQA Using Lexical Based Inference Extraction

Abstract Views: 331  |  PDF Views: 2

Authors

Renita Raymond
Computer Science and Engineering Department, Anand institute of Higher Technology, Chennai, Tamil Nadu, India
Karnavel Kuppusamy
Computer Science and Engineering Department, Anand institute of Higher Technology, Chennai, Tamil Nadu, India

Abstract


This paper presents an enhanced approach for Question Classification and Answer Extraction in Restricted Domain Question Answering (RDQA). Question Classification and Answer Extraction is the core problem of RDQA and determines the performance of the Question Answering in the Restricted Domain. The proposed approach improves the performance of RDQA by means of (1) Question type prediction model based on Bayesian classification (2) Lexicalized-Index based Passage Retrieval (3) Lexical-Semantic based Inference Extraction. This paper also describes usercentered task-based evaluations for Answer Validation. Further improvements are achieved by combining our model with the classic one to improve the performance of Restricted Domain Question Answering.

Keywords


Restricted Domain Question Answering (RDQA), Bayesian Classification, Passage Retrieval, Answer Extraction, Text Inference.

References