Improving web search ranking by incorporating user behavior information Export

@inproceedings{citeulike:1284298, abstract = {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.}, address = {New York, NY, USA}, author = {Agichtein, Eugene and Brill, Eric and Dumais, Susan}, booktitle = {SIGIR '06: Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval}, citeulike-article-id = {1284298}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1148170.1148177}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1148170.1148177}, doi = {10.1145/1148170.1148177}, isbn = {1-59593-369-7}, keywords = {navigation, personalization, web-search}, location = {Seattle, Washington, USA}, pages = {19--26}, posted-at = {2009-01-21 17:01:01}, priority = {3}, publisher = {ACM}, title = {Improving web search ranking by incorporating user behavior information}, url = {http://dx.doi.org/10.1145/1148170.1148177}, year = {2006} }

TY - CONF ID - citeulike:1284298 L3 - citeulike-article-id:1284298 N2 - 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. CY - Seattle, Washington, USA SN - 1-59593-369-7 AD - New York, NY, USA EP - 26 TI - Improving web search ranking by incorporating user behavior information PB - ACM T2 - SIGIR '06: Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval SP - 19 KW - navigation KW - personalization KW - web-search AU - Agichtein, Eugene AU - Brill, Eric AU - Dumais, Susan PY - 2006/// UR - http://dx.doi.org/10.1145/1148170.1148177 ER -