Improving web search ranking by incorporating user behavior information
E Agichtein, E Brill, S Dumais - … of the 29th annual international ACM …, 2006 - dl.acm.org
E Agichtein, E Brill, S Dumais
Proceedings of the 29th annual international ACM SIGIR conference on …, 2006•dl.acm.orgWe 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 …
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 …
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.
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