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Metadata-Aware Measures for Answer Summarization in Community Question Answering
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology.
2011 (English)Independent thesis Advanced level (degree of Master (Two Years)), 30 credits / 45 HE creditsStudent thesis
Abstract [en]

My thesis report presents a framework for automatically processing information coming from community Question Answering (cQA) portals. The purpose is that of automatically generating a summary in response to a question posed by a human user in natural language. The goal is to ensure that such answer be as trustful, complete, relevant and succinct as possible. In order to do so, the author exploits the metadata intrinsically present in User Generated Content (UGC) to bias automatic multi-document summarization techniques toward higher quality information. The originality of this work lies in the fact that it adopts a representation of concepts alternative to n-grams, which is the standard choice for text summarization tasks; furthermore it proposes two concept-scoring functions based on the notion of semantic overlap. Experimental results on data drawn from Yahoo! Answers demonstrate the effectiveness of the presented method in terms of ROUGE scores. This shows that the information contained in the best answers voted by users of cQA portals can be successfully complemented by the proposed method.

Place, publisher, year, edition, pages
2011.
Series
IT ; 11 003
Identifiers
URN: urn:nbn:se:uu:diva-146634OAI: oai:DiVA.org:uu-146634DiVA, id: diva2:398628
Uppsok
Technology
Supervisors
Examiners
Available from: 2011-02-18 Created: 2011-02-18 Last updated: 2011-02-18Bibliographically approved

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