A comprehensive analysis of parameter settings for novelty-biased cumulative gain

ACM International Conference Proceeding Series

Volumn , Issue , 2012, Pages 1950-1954

  Leelanupab, Teerapong ^a   Zuccon, Guido ^b   Jose, Joemon M ^c  

^a KING MONGKUT'S INSTITUTE OF TECHNOLOGY LADKRABANG   (Thailand)

^b CSIRO   (Australia)

^c UNIVERSITY OF GLASGOW   (United Kingdom)

Author keywords

diversity; evaluation measure

Indexed keywords

COMPREHENSIVE ANALYSIS; DIVERSITY; EVALUATION MEASURES; PARAMETER SETTING; RETRIEVAL PERFORMANCE;

KNOWLEDGE MANAGEMENT;

INFORMATION RETRIEVAL;

EID: 84871050880     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2396761.2398550     Document Type: Conference Paper

References (15)

1. B. Carterette. System effectiveness, user models, and user utility: a conceptual framework for investigation. In SIGIR '11, pages 903-912, 2011.
2. O. Chapelle, D. Metlzer, Y. Zhang, and P. Grinspan. Expected reciprocal rank for graded relevance. In CIKM '09, pages 621-630, 2009.
3. C. L. Clarke, N. Craswell, and I. Soboroff. Overview of the trec 2009 web track. In TREC 18, 2009.
4. C. L. Clarke, M. Kolla, G. V. Cormack, O. Vechtomova, A. Ashkan, S. Büttcher, and I. MacKinnon. Novelty and diversity in information retrieval evaluation. In SIGIR '08, pages 659-666, 2008.
5. C. L. Clarke, M. Kolla, and O. Vechtomova. An effectiveness measure for ambiguous and underspecified queries. In ICTIR '09, pages 188-199, 2009.
6. T. Leelanupab, G. Zuccon, and J. M. Jose. A query-basis approach to parametrizing novelty-biased cumulative gain. In ICTIR '11, pages 327-331, 2011.
7. T. Leelanupab. A Ranking Framework and Evaluation for Diversity-Based Retrieval. PhD thesis, School of Computing Science, University of Glasgow, 2012.
8. F. Radlinski, P. N. Bennett, B. Carterette, and T. Joachims. Redundancy, diversity and interdependent document relevance. ACM SIGIR Forum, 43:46-52, 2009.
9. S. E. Robertson, M. Maron, and W. Cooper. Probability of Relevance: A Unification of two Competing Models for Document Retrieval. Information technology: research and development, pages 1-21, 1982.
10. T. Sakai. Evaluating evaluation metrics based on the bootstrap. In SIGIR '06, pages 525-532, 2006.
11. T. Sakai, N. Craswell, R. Song, S. Robertson, Z. Dou, and C. Y. Lin. Simple evaluation metrics for diversified search results. In EVIA '10, pages 42-50, 2010.
12. T. Sakai and R. Song. Evaluating diversified search results using per-intent graded relevance. In SIGIR '11, pages 1043-1052, Beijing, China, 2011.
13. E. Yilmaz, J. Aslam, and S. Robertson. A new rank correlation coefficient for information retrieval. In SIGIR '08, pages 587-594, 2008.
14. C. X. Zhai, W. W. Cohen, and J. Lafferty. Beyond independent relevance: methods and evaluation metrics for subtopic retrieval. In SIGIR '03, pages 10-17, 2003.
15. G. Zuccon. Ranking Documents with Quantum Probabilities. PhD thesis, School of Computing Science, University of Glasgow, 2012.