Abstract: Question answering is the most common technique to collect information from different sources. One such source which gave rise in recent internet technology is Community Question Answering (cQA). Earlier the cQA gave information only in textual format which is not very much informative for many questions posted by the user, however it is natural to extend text based question answering research to Multimedia Question Answering which gave importance for many reasons. First most video contents are indexed with metadata, second many questions are better explained with the help of non textual medium, third media contents especially videos are now used to convey many types of information. In this project a technique is proposed which enriches textual answers with appropriate media data. This technique consists of three components to enrich textual data: Answer medium selection, Query generation for multimedia search, Multimedia data selection and Presentation. The multimedia question answering complements text QA with whole QA paradigm i.e., image video along with text. This approach or technique automatically selects media information for appropriate textual answer questioned by users or community members. Here Question answering languages leverages advance media content, linguistic analysis, and domain knowledge to return precise answers to questions posted by community members.
Keywords: Question Answering, Answer Medium Selection
Title: Generating Multimedia Information Using Web Data mining
Author: SharathBabu.S, Ravi.M
International Journal of Computer Science and Information Technology Research
ISSN 2348-120X (online), ISSN 2348-1196 (print)
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