Diversifying web search results

Result diversity is a topic of great importance as more facets of queries are discovered and users expect to find their desired facets in the first page of the results. However, the underlying questions of how ‘diversity’ interplays with ‘quality’ and when preference should be given to one or both are not well-understood. In this work, we model the problem as expectation maximization and study the challenges of estimating the model parameters and reaching an equilibrium. One model parameter, for example, is correlations between pages which we estimate using textual contents of pages and click data (when available). We conduct experiments on diversifying randomly selected queries from a query log and the queries chosen from the disambiguation topics of Wikipedia. Our algorithm improves upon Google in terms of the diversity of random queries, retrieving 14% to 38% more aspects of queries in top 5, while maintaining a precision very close to Google. On a more selective set of q...

• Type: Conference
• Year: 2010
• Where: WWW
• Authors: Davood Rafiei, Krishna Bharat, Anand Shukla
• Keywords: Internet Technology, Model Parameter, Pages, Random Queries, WWW 2010