Combining CORI and the decision-theoretic approach for advanced resource selection

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2997, Issue , 2004, Pages 138-153

  Nottelmann, Henrik ^a   Fuhr, Norbert ^a  

^a UNIVERSITY OF DUISBURG ESSEN   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTERS;

DECISION THEORETIC APPROACH; DECISION-THEORETIC; LOGISTIC FUNCTIONS; RELEVANT DOCUMENTS; RESOURCE RANKING; RESOURCE SELECTION; RETRIEVAL QUALITY; STATE-OF-THE-ART SYSTEM;

HEURISTIC METHODS;

EID: 34547657537     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-24752-4_11     Document Type: Article

References (17)

1. J. Callan and M. Connell. Query-based sampling of text databases. ACM Transactions on Information Systems, 19(2):97-130, 2001.
2. J. Callan, G. Cormack, C. Clarke, D. Hawking, and A. Smeaton, editors. Proceedings of the 26st Animal International ACM SIGIR Conference on Research and Development in Information Retrieval, New York, 2003. ACM.
3. J. Callan, Z. Lu, and W. Croft. Searching distributed collections with inference networks. In E. Fox, P. Ingwersen, and R. Fidel, editors, Proceedings of the 18th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 21-29, New York, 1995. ACM. ISBN 0-89791-714-6.
4. J. Callan, A. L. Powell, J. C. French, and M. Connell. The effects of query-based sampling on automatic database selection algorithms. ACM Transactions on Information Systems (submitted for publication).
5. J. French, A. Powell, J. Callan, C. Viles, T. Emmitt, K. Prey, and Y. Mou. Comparing the performance of database selection algorithms. In Proceedings of the 22nd International Conference on Research and Development in Information Retrieval, pages 238-245, New York, 1999. ACM.
6. N. Fuhr. A decision-theoretic approach to database selection in networked IR. ACM Transactions on Information Systems, 17(3):229-249, 1999.
7. L. Gravano and H. Garcia-Molina. Generalizing GIOSS to vector-space databases and broker hierarchies. In U. Dayal, P. Gray, and S. Nishio, editors, VLDB'95, Proceedings of 21th International Conference on Very Large Data Bases, pages 78-89, Los Altos, California, 1995. Morgan Kaufman.
8. D. Harman, editor. The Second Text REtrieval Conference (TREC-2), Gaithersburg, Md. 20899, 1994. National Institute of Standards and Technology.
9. H. Nottelmann and N. Fuhr. Evaluating different methods of estimating retrieval quality for resource selection. In Callan et al. [2].
10. H. Nottelmann and N. Fuhr. From uncertain inference to probability of relevance for advanced IR applications. In F. Sebastiani, editor, 25th European Conference on Information Retrieval Research (ECIR 2003), pages 235-250, Heidelberg et al., 2003. Springer.
11. W. H. Press, S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery, editors. Nested Relations and Complex Objects in Databases. Cambridge University Press, 1992.
12. S. E. Robertson, S. Walker, M. Hancock-Beaulieu, A. Gull, and M. Lau. Okapi at TREC. In Text REtrieval Conference, pages 21-30, 1992.
13. L. Si and J. Callan. Relevant document distribution estimation method for resource selection. In Callan et al. [2].
14. L. Si, R. Jin, J. Callan, and P. Ogilvie. Language model framework for resource selection and results merging. In D. Grossman, editor, Proceedings of the 11th International Conference on Information and Knowledge Management, New York, 2002. ACM. http://www-2.cs.cmu.edu/callan/Papers/cikm02-lsi.pdf.
15. C. J. van Rijsbergen. A non-classical logic for information retrieval. The Computer Journal, 29(6):481-485, 1986.
16. C. J. van Rijsbergen. Probabilistic retrieval revisited. The Computer Journal, 35(3):291-298, 1992.
17. S. Wong and Y. Yao. On modeling information retrieval with probabilistic inference. ACM Transactions on Information Systems, 13(1):38-68, 1995.