Search engines that learn from implicit feedback

Computer

Volumn 40, Issue 8, 2007, Pages 34-40

  Joachims, Thorsten ^a   Radlinski, Filip ^a  

^a Department of Computer Science and School of Operations Research and Information Engineering   (United States)

Author keywords

Machine learning; Osmot engine; Pairwise preferences; Search

Indexed keywords

EID: 34548215752     PISSN: 00189162     EISSN: None     Source Type: Trade Journal    
DOI: 10.1109/MC.2007.289     Document Type: Article

References (12)

1. J. Teevan, S.T. Dumais, and E. Horvitz, "Characterizing the Value of Personalizing Search," to be published in Proc. ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR 07), ACM Press, 2007.
2. F. Radlinski and T. Joachims, "Query Chains: Learning to Rank from Implicit Feedback," Proc. ACM SIGKDD Int'l Conf. Knowledge Discovery and Data Mining (KDD 05), ACM Press, 2005, pp. 239-248.
3. T. Joachims et al., "Evaluating the Accuracy of Implicit Feedback from Clicks and Query Reformulations in Web Search," ACM Trans. Information Systems, vol. 25, no. 2, article 7, 2007.
4. F. Radlinski and T. Joachims, "Minimally Invasive Randomization for Collecting Unbiased Preferences from Clickthrough Logs," Proc. Nat'l Conf. Am. Assoc. for Artificial Intelligence (AAAI 06), AAAI, 2006, pp. 1406-1412.
5. F. Radlinski and T. Joachims, "Active Exploration for Learning Rankings from Clickthrough Data," to be published in Proc. ACM SIGKDD Int'l Conf. Knowledge Discovery and Data Mining (KDD 07), ACM Press, 2007.
6. T. Joachims, "Optimizing Search Engines Using Clickthrough Data," Proc. ACM SIGKDD Int'l Conf. Knowledge Discovery and Data Mining (KDD 02), ACM Press, 2002, pp. 132-142.
7. D. Kelly and J. Teevan, "Implicit Feedback for Inferring User Preference: A Bibliography," ACM SIGIR Forum, vol. 37, no. 2, 2003, pp. 18-28.
8. E. Agichtein, E. Brill, and S. Dumais, "Improving Web Search Ranking by Incorporating User Behavior," Proc. ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR 06), ACM Press, 2006, pp. 19-26.
9. G. Furnas, "Experience with an Adaptive Indexing Scheme," Proc. ACM SIGCHI Conf. Human Factors in Computing Systems (CHI 85), ACM Press, 1985, pp. 131-135.
10. W.W. Cohen, R.E. Shapire, and Y. Singer, "Learning to Order Things," J. Artificial Intelligence Research, vol. 10, AI Access Foundation, Jan.-June 1999, pp. 243-270.
11. V. Vapnik, Statistical Learning Theory, John Wiley & Sons, 1998.
12. R. Herbrich, T. Graepel, and K. Obermayer, "Large-Margin Rank Boundaries for Ordinal Regression," P. Bartlett et al., eds., Advances in Large-Margin Classifiers, MIT Press, 2000, pp. 115-132.