On the informativeness of cascade and intent-aware effectiveness measures

Proceedings of the 20th International Conference on World Wide Web, WWW 2011

Volumn , Issue , 2011, Pages 407-416

  Ashkan, Azin ^a   Clarke, Charles L A ^a  

^a UNIVERSITY OF WATERLOO   (Canada)

Author keywords

Diversity; Effectiveness measures; Evaluation; Measure informativeness; Novelty

Indexed keywords

DIVERSITY; EFFECTIVENESS MEASURE; EVALUATION; INFORMATIVENESS; NOVELTY;

SEARCH ENGINES; WORLD WIDE WEB;

MAXIMUM ENTROPY METHODS;

EID: 84871631227     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1963405.1963464     Document Type: Conference Paper

References (21)

1. nd ACM International Conference on Web Search and Data Mining, pages 5-14, 2009.
2. th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 27-34, 2005.
3. rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 33-40, 2000.
4. th ACM Conference on Information and Knowledge Management, pages 621-630, 2009.
5. th Text REtrieval Conference, 2009.
6. C. L. A. Clarke, N. Craswell, I. Soboroff, and A. Ashkan. A comparative analysis of cascade measures for novelty and diversity. In ACM International Conference on Web Search and Data Mining, 2011.
7. st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 659-666, 2008.
8. nd International Conference on the Theory of Information Retrieval, pages 188-199, 2009.
9. T. Cover and J. Thomas. Elements of information theory. Wiley-Interscience, 2006.
10. N. Craswell, O. Zoeter, M. J. Taylor, and B. Ramsey. An experimental comparison of click position-bias models. In International Conference on Web Search and Web Data Mining, pages 87-94, 2008.
11. K. Järvelin and J. Kekäläinen. Cumulated gain-based evaluation of IR techniques. ACM Transactions on Information Systems, 20(4):422-446, 2002.
12. A. Moffat and J. Zobel. Rank-biased precision for measurement of retrieval effectiveness. ACM Transactions on Information Systems, 27(1):1-27, 2008.
13. M. Powell. A fast algorithm for nonlinearly constrained optimization calculations. Numerical Analysis, pages 144-157, 1978.
14. rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 853-854, 2010.
15. rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 603-610, 2010.
16. th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, page 532, 2006.
17. T. Sakai. On the robustness of information retrieval metrics to biased relevance assessments. Information and Media Technologies, 4(2):547-557, 2009.
18. th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 162-169, 2005.
19. E. Yilmaz and S. Robertson. On the choice of effectiveness measures for learning to rank. Information Retrieval, 13(3):271-290, 2010.
20. E. Yilmaz, M. Shokouhi, N. Craswell, and S. Robertson. Incorporating user behavior information in IR evaluation. In SIGIR 2009 Workshop on Understanding the User: Logging and Interpreting User Interactions in Information Retrieval, 2009.
21. Y. Zhang, L. Park, and A. Moffat. Click-based evidence for decaying weight distributions in search effectiveness metrics. Information Retrieval, 13(1):46-69, 2010. WWW 2011 - Session: Evaluation March 28-April 1, 2011, Hyderabad, India 416.