Study on question-answering system based on Meta search engine
Fei Li, Haiyan Kang, Yangsen Zhang, Wenjie Su
Abstract
Fei Li, Haiyan Kang, Yangsen Zhang, Wenjie Su
Abstract
Meta search engine which can provide rich information is obviously an ideal source of answers to many types of questions. This paper describes a question answering system based on web, and puts forward to a new method to search information based on Meta search engine and new word discovery. In the information retrieval module, N-gram model and web pages which get from search engine are used to find new words. Experiments show that the addition of new words discovery not only greatly improves the precision of documents retrieval in the module of information retrieval, but also improves the accuracy of answer extraction.
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Meta search engine which can provide rich information is obviously an ideal source of answers to many types of questions. This paper describes a question answering system based on web, and puts forward to a new method to search information based on Meta search engine and new word discovery. In the information retrieval module, N-gram model and web pages which get from search engine are used to find new words. Experiments show that the addition of new words discovery not only greatly improves the precision of documents retrieval in the module of information retrieval, but also improves the accuracy of answer extraction.
Key concepts: Question answering, Information retrieval, Search engine, Computer science, Metasearch engine, Web search engine, Search analytics, World Wide Web