Congratulations to Yasser Ganjisffar on passing his advancement to candidacy exam!

Thesis: On Improving Search in Wikipedia

Committee:
Crista Lopes (Chair)
Faryar Jabbari
Ramesh Jain
Jim Jones
Don Patterson

Wikipedia, the largest encyclopedia on the Web, is often seen as the most successful example of crowdsourcing. The encyclopedic knowledge it accumulated over the years is so large that one often uses search engines, to find information in it. In contrast to regular Web pages, Wikipedia is fairly structured, and articles are usually accompanied with history pages, categories and talk pages. The meta–data available in these pages can be analyzed to gain a better understanding of the content and quality of the articles. We analyze the quality of search results of the current major Web search engines (Google, Yahoo! and Live) in Wikipedia. We discuss how the rich meta–data available in wiki pages can be used to provide better search results in Wikipedia. Built on the studies on “Wisdom of Crowd” and the effectiveness of the knowledge collected by a large number of people, we investigate the effect of incorporating the extent of review of an article in the quality of rankings of the search results. The ex- tent of review is measured by the number of distinct editors contributed to the articles and is extracted by processing Wikipedia’s history pages. Our experimental results show that re–ranking search results of the three major Web search engines using the review feature improves quality of their rankings for Wikipedia–specific searches. We also compare the effectiveness of the proposed review–based ranking with PageRank based ranking.