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A Hybrid Optimization Technique for Effective Document Clustering in Question Answering System


Affiliations
1 Department of Master of Computer Applications, Dr. Mahalingam College of Engineering and Technology, India
2 Department of Computer Science and Engineering, Institute of Road and Transport Technology, India
     

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Today, the information is growing enormously and it is difficult and tedious task to retrieve the necessary information from that pool. The main area for retrieving relevant answers is called intelligent information retrieval. To achieve this, question and answering system is used. This question and answering plays a major role in user query processing, information retrieval and extracting related information from the information pool. Recently, number of optimization algorithms is introduced to obtain the accurate and better results. Genetic Algorithm and Cuckoo Search are nature inspired meta-heuristic optimization algorithms. In this paper, combination of Genetic Algorithm with Cuckoo Search is applied to the question and answering system. The proposed algorithm is tested with the Amazon review, Trip Advisor and 20 news group data sets. The results are compared with Genetic Algorithm and Cuckoo Search algorithms.

Keywords

Document Clustering, Cuckoo Search, Genetic Algorithm, Information Retrieval, Question and Answering.
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  • A Hybrid Optimization Technique for Effective Document Clustering in Question Answering System

Abstract Views: 503  |  PDF Views: 4

Authors

K. Karpagam
Department of Master of Computer Applications, Dr. Mahalingam College of Engineering and Technology, India
A. Saradha
Department of Computer Science and Engineering, Institute of Road and Transport Technology, India

Abstract


Today, the information is growing enormously and it is difficult and tedious task to retrieve the necessary information from that pool. The main area for retrieving relevant answers is called intelligent information retrieval. To achieve this, question and answering system is used. This question and answering plays a major role in user query processing, information retrieval and extracting related information from the information pool. Recently, number of optimization algorithms is introduced to obtain the accurate and better results. Genetic Algorithm and Cuckoo Search are nature inspired meta-heuristic optimization algorithms. In this paper, combination of Genetic Algorithm with Cuckoo Search is applied to the question and answering system. The proposed algorithm is tested with the Amazon review, Trip Advisor and 20 news group data sets. The results are compared with Genetic Algorithm and Cuckoo Search algorithms.

Keywords


Document Clustering, Cuckoo Search, Genetic Algorithm, Information Retrieval, Question and Answering.

References