Abstract
We study an explicit parametric model of documents, queries, and relevancy assessment for Information Retrieval (IR). Mean-field methods are applied to analyze the model and derive efficient practical algorithms to estimate the parameters in the problem. The hyperparameters are estimated by a fast approximate leave-one-out cross-validation procedure based on the cavity method. The algorithm is further evaluated on several benchmark databases by comparing with standard algorithms in IR.
Original language | English |
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Title of host publication | NIPS 2002 |
Subtitle of host publication | Proceedings of the 15th International Conference on Neural Information Processing Systems |
Editors | Suzanna Becker, Sebastian Thrun, Klaus Obermayer |
Publisher | MIT Press Journals |
Pages | 497-504 |
Number of pages | 8 |
ISBN (Electronic) | 0262025507, 9780262025508 |
State | Published - 2002 |
Externally published | Yes |
Event | 15th International Conference on Neural Information Processing Systems, NIPS 2002 - Vancouver, Canada Duration: 9 Dec 2002 → 14 Dec 2002 |
Publication series
Name | NIPS 2002: Proceedings of the 15th International Conference on Neural Information Processing Systems |
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Conference
Conference | 15th International Conference on Neural Information Processing Systems, NIPS 2002 |
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Country/Territory | Canada |
City | Vancouver |
Period | 9/12/02 → 14/12/02 |
Bibliographical note
Publisher Copyright:© NIPS 2002: Proceedings of the 15th International Conference on Neural Information Processing Systems. All rights reserved.
ASJC Scopus subject areas
- Signal Processing
- Computer Networks and Communications
- Information Systems