QA Generation Using Multimedia Based Harvesting Web Information | Abstract

ISSN ONLINE(2320-9801) PRINT (2320-9798)

Research Article Open Access

QA Generation Using Multimedia Based Harvesting Web Information

Abstract

Along with the proliferation and improvement of underlying communication technologies, community QA (cQA) has emerged as an extremely popular alternative to acquire information online, owning to the following facts. First, information seekers are able to post their specific questions on any topic and obtain answers provided by other participants. By leveraging community efforts, they are able to get better answers than simply using search engines. Second, in comparison with automated QA systems, cQA usually receives answers with better quality as they are generated based on human intelligence. Third, over times, a tremendous number of QA pairs have been accumulated in their repositories, and it facilitates the preservation and search of answered questions. For example, Wiki Answer, one of the most well-known cQA systems, hosts more than 13 million answered questions distributed in 7,000 categories (as of August 2011).

S.Jensy Mary, A.S Syed Navaz & J.Antony Daniel Rex

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