%0 Conference Paper %1 citeulike:4374823 %A Chapelle, Olivier %A Zhang, Ya %B Proceedings of the 18th International Conference on World Wide Web %C New York, NY, USA %D 2009 %I ACM %K click-model social-search %P 1--10 %R 10.1145/1526709.1526711 %T A Dynamic Bayesian Network Click Model for Web Search Ranking %U http://dx.doi.org/10.1145/1526709.1526711 %X As with any application of machine learning, web search ranking requires labeled data. The labels usually come in the form of relevance assessments made by editors. Click logs can also provide an important source of implicit feedback and can be used as a cheap proxy for editorial labels. The main difficulty however comes from the so called position bias - urls appearing in lower positions are less likely to be clicked even if they are relevant. In this paper, we propose a Dynamic Bayesian Network which aims at providing us with unbiased estimation of the relevance from the click logs. Experiments show that the proposed click model outperforms other existing click models in predicting both click-through rate and relevance. %@ 978-1-60558-487-4

@inproceedings{citeulike:4374823, abstract = {{As with any application of machine learning, web search ranking requires labeled data. The labels usually come in the form of relevance assessments made by editors. Click logs can also provide an important source of implicit feedback and can be used as a cheap proxy for editorial labels. The main difficulty however comes from the so called position bias - urls appearing in lower positions are less likely to be clicked even if they are relevant. In this paper, we propose a Dynamic Bayesian Network which aims at providing us with unbiased estimation of the relevance from the click logs. Experiments show that the proposed click model outperforms other existing click models in predicting both click-through rate and relevance.}}, added-at = {2017-11-15T17:02:25.000+0100}, address = {New York, NY, USA}, author = {Chapelle, Olivier and Zhang, Ya}, biburl = {https://www.bibsonomy.org/bibtex/2a90b91a19a92772a36a01b18ae4614eb/brusilovsky}, booktitle = {Proceedings of the 18th International Conference on World Wide Web}, citeulike-article-id = {4374823}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1526709.1526711}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1526709.1526711}, doi = {10.1145/1526709.1526711}, interhash = {95a10ad6ba048092c747286c234fbbad}, intrahash = {a90b91a19a92772a36a01b18ae4614eb}, isbn = {978-1-60558-487-4}, keywords = {click-model social-search}, location = {Madrid, Spain}, pages = {1--10}, posted-at = {2017-04-07 04:30:27}, priority = {2}, publisher = {ACM}, series = {WWW '09}, timestamp = {2020-03-05T22:22:36.000+0100}, title = {{A Dynamic Bayesian Network Click Model for Web Search Ranking}}, url = {http://dx.doi.org/10.1145/1526709.1526711}, year = 2009 }