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• W2402644936 abstract "We studied the problem of searching answers for questions on a Question-and-Answer Website from knowledge bases. A number of research e↵orts had been developed using Stack Overflow data, which is available for the public. Surprisingly, only a few papers tried to improve the search for better answers. Furthermore, current approaches for searching a Question-and-Answer Website are usually limited to the question database, which is usually the website own content. We showed it is feasible to use knowledge bases as sources for answers. We implemented both vector-space and topic-space representations for our datasets and compared these distinct techniques. Finally, we proposed a hybrid ranking approach that took advantage of a machine-learned classifier to incorporate the tag information into the ranking and showed that it was able to improve the retrieval performance." @default.
• W2402644936 created "2016-06-24" @default.
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• W2402644936 date "2016-01-01" @default.
• W2402644936 modified "2023-09-26" @default.
• W2402644936 title "Mining Knowledge Bases for Question & Answers Websites" @default.
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• W2402644936 hasPublicationYear "2016" @default.
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