NDLI: Incorporating Participant Reputation in Community-Driven Question Answering Systems

Content Provider	IEEE Xplore Digital Library
Author	Liangjie Hong Zaihan Yang Davison, B.D.
Copyright Year	2009
Abstract	Community-driven Question Answering services are gaining increasing attention with tens of millions of users and hundreds of millions of posts in recent years. Due to its size, there is a need for users to be able to search these large question answer archives and retrieve high quality content. Research work shows that user reputation modeling makes a contribution when incorporated with relevance models. However, the effectiveness of different link analysis approaches and how to embed topical information---as a user may have different expertise in various areas---are still open questions. In this work, we address these two research questions by first reviewing different link analysis schemes---especially discussing the use of PageRank-based methods since they are less commonly utilized in user reputation modeling. We also introduce Topical PageRank analysis for modeling user reputation on different topics. Comparative experimental results on data from Yahoo! Answers show that PageRank-based approaches are more effective than HITS-like schemes and other heuristics, and that topical link analysis can improve performance.
Starting Page	475
Ending Page	480
File Size	238758
Page Count	6
File Format	PDF
ISBN	9781424453344
DOI	10.1109/CSE.2009.28
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-08-29
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer science Link Analysis Content based retrieval Natural languages Web pages Search engines Question Answering Performance analysis Portals Information analysis Context modeling User Reputation
Content Type	Text
Resource Type	Article

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