Community-based snippet-indexes for pseudo-anonymous personalization in web search

Oisín Boydell, Barry Smyth
2006 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '06  
We describe and evaluate an approach to personalizing Web search that involves post-processing the results returned by some underlying search engine so that they reflect the interests of a community of like-minded searchers. To do this we leverage the search experiences of the community by mining the title and snippet texts of results that have been selected by community members in response to their queries. Our approach seeks to build a community-based snippet index that reflects the evolving
more » ... nterests of a group of searchers. This index is then used to re-rank the results returned by the underlying search engine by boosting the ranking of key results that have been frequently selected for similar queries by community members in the past.
doi:10.1145/1148170.1148283 dblp:conf/sigir/BoydellS06 fatcat:4j2z5xgisbakvprm2ad7wieqxa