Improving web search ranking by incorporating user behavior information

We show that incorporating user behavior data can significantly improve ordering of top results in real web search setting. We examine alternatives for incorporating feedback into the ranking process and explore the contributions of user feedback compared to other common web search features. We report results of a large scale evaluation over 3,000 queries and 12 million user interactions with a popular web search engine. We show that incorporating implicit feedback can augment other features, improving the accuracy of a competitive web search ranking algorithms by as much as 31% relative to the original performance. Categories and Subject Descriptors H.3.3 Information Search and Retrieval – Relevance feedback, search process; H.3.5 Online Information Services – Web-based services. General Terms Algorithms, Measurement, Experimentation Keywords Web search, implicit relevance feedback, web search ranking.

• Type: Conference
• Year: 2006
• Where: SIGIR
• Authors: Eugene Agichtein, Eric Brill, Susan T. Dumais
• Keywords: Relevance Feedback, SIGIR 2006, Web Search, Web Search Ranking