On Improving Wikipedia Search using Article Quality
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 inexperienc...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2007
|
| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/1264 https://ink.library.smu.edu.sg/context/sis_research/article/2263/viewcontent/improveWikiSearch.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Singapore Management University |
| Language: | English |
| Summary: | 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. |
|---|