NDLI: Multimedia answering: enriching text QA with media information

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Multimedia answering: enriching text QA with media information

Content Provider	ACM Digital Library
Author	Chua, Tat-Seng Wang, Meng Nie, Liqiang Li, Guangda Zha, Zhengjun
Abstract	Existing community question-answering forums usually provide only textual answers. However, for many questions, pure texts cannot provide intuitive information, while image or video contents are more appropriate. In this paper, we introduce a scheme that is able to enrich text answers with image and video information. Our scheme investigates a rich set of techniques including question/answer classification, query generation, image and video search reranking, etc. Given a question and the community-contributed answer, our approach is able to determine which type of media information should be added, and then automatically collects data from Internet to enrich the textual answer. Different from some efforts that attempt to directly answer questions with image and video data, our approach is built based on the community-contributed textual answers and thus it is more feasible and able to deal with more complex questions. We have conducted empirical study on more than 3,000 QA pairs and the results demonstrate the effectiveness of our approach.
Starting Page	695
Ending Page	704
Page Count	10
File Format	PDF
ISBN	9781450307574
DOI	10.1145/2009916.2010010
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2011-07-24
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Cqa Medium selection Question answering Reranking
Content Type	Text
Resource Type	Article

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