Improving personalized web search using result diversification

  • Authors:
  • Filip Radlinski;Susan Dumais

  • Affiliations:
  • Cornell University, Ithaca, NY;Microsoft Research, Redmond, WA

  • Venue:
  • SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
  • Year:
  • 2006

Quantified Score

Hi-index 0.02

Visualization

Abstract

We present and evaluate methods for diversifying search results to improve personalized web search. A common personalization approach involves reranking the top N search results such that documents likely to be preferred by the user are presented higher. The usefulness of reranking is limited in part by the number and diversity of results considered. We propose three methods to increase the diversity of the top results and evaluate the effectiveness of these methods.