论文信息 - Language Modeling and Relevance

Language Modeling and Relevance

Relevance is a basic concept in information retrieval, but its role in the languagemodeling approach to retrieval is not completely straightforward. We examine the issues involved, especially in dealing with multiple relevant documents and in applying relevance feedback, and consider various strategies for developing the language modeling approach to accommodate multiple, rather than single, relevant documents in a theoretically principled way.

[1] Richard M. Schwartz,et al. Probabilistic models for topic detection and tracking , 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).

[2] W. Bruce Croft. Advances in Informational Retrieval: Recent Research from the Center for Intelligent Information Retrieval , 2000 .

[3] Stephen E. Robertson,et al. A probabilistic model of information retrieval: development and comparative experiments - Part 1 , 2000, Inf. Process. Manag..

[4] K. Sparck Jones,et al. A Probabilistic Model of Information Retrieval : Development and Status , 1998 .

[5] Djoerd Hiemstra,et al. Term-specific smoothing for the language modeling approach to information retrieval: the importance of a query term , 2002, SIGIR '02.

[6] W. Bruce Croft,et al. Text retrieval and inference , 1992 .

[7] Jay Ponte,et al. LANGUAGE MODELS FOR RELEVANCE FEEDBACK , 2002 .

[8] Stefano Mizzaro. Relevance: the whole history , 1997 .

[9] Richard M. Schwartz,et al. Topic tracking for radio, TV broadcast, and newswire , 1999, EUROSPEECH.

[10] Tefko Saracevic,et al. RELEVANCE: A review of and a framework for the thinking on the notion in information science , 1997, J. Am. Soc. Inf. Sci..

[11] Peter Norvig,et al. Text-Based Intelligent Systems , 1994, Artif. Intell..

[12] Richard M. Schwartz,et al. A hidden Markov model information retrieval system , 1999, SIGIR '99.