Publication Type

Conference Proceeding Article

Publication Date

11-2007

Abstract

Wikipedia is presently the largest free-and-open online encyclopedia collaboratively edited and maintained by volunteers. While Wikipedia offers full-text search to its users, the accuracy of its relevance-based search can be compromised by poor quality articles edited by non-experts and inexperienced contributors. In this paper, we propose a framework that re-ranks Wikipedia search results considering article quality. We develop two quality measurement models, namely Basic and PeerReview, to derive article quality based on co-authoring data gathered from articles' edit history. Compared with Wikipedia's full-text search engine, Google and Wikiseek, our experimental results showed that (i) quality-only ranking produced by PeerReview gives comparable performance to that of Wikipedia and Wikiseek; (ii) PeerReview combined with relevance ranking outperforms Wikipedia's full-text search significantly, delivering search accuracy comparable to Google.

Discipline

Databases and Information Systems | Numerical Analysis and Scientific Computing

Research Areas

Data Management and Analytics

Publication

WIDM '07: Proceedings of the 9th Annual ACM International Workshop on Web Information and Data Management: November 9, 2007, Lisbon, Portugal

First Page

145

Last Page

152

ISBN

9781595938299

Identifier

10.1145/1316902.1316926

Publisher

ACM

City or Country

New York

Additional URL

http://dx.doi.org/10.1145/1316902.1316926

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