CS计算机代考程序代写 information retrieval javascript database Java AI algorithm The use of MMR, diversity-based reranking for reordering documents and producing summaries | Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval

The use of MMR, diversity-based reranking for reordering documents and producing summaries | Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval

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HomeConferencesIRProceedingsSIGIR ’98The use of MMR, diversity-based reranking for reordering documents and producing summaries

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The use of MMR, diversity-based reranking for reordering documents and producing summaries

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Authors:
Jaime Carbonell
Language Technologies Institute, Carnegie Mellon University

Language Technologies Institute, Carnegie Mellon University
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,
Jade Goldstein
Language Technologies Institute, Carnegie Mellon University

Language Technologies Institute, Carnegie Mellon University
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SIGIR ’98: Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrievalAugust 1998 Pages 335–336https://doi.org/10.1145/290941.291025

Published:01 August 1998

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SIGIR ’98: Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
The use of MMR, diversity-based reranking for reordering documents and producing summariesPages 335–336

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References

1.Buckley C. implementation of the smart information retrieval system. Technical Report Tit 85-686, Cornell University. Google ScholarDigital Library
2.J.G.Carbonell, Y. Geng, and J. Goldstein. Automated query-relevant summarization and diversity-based reranking. In 15th International Joint ConJerence on Artificial Intelligence, Workshop: AI in Digital Libraries, pages 9- 14, Nagoya, Japan, August 1997.Google Scholar
3.J.M. Kupiec, J. Pedersen, and F. Chen. A trainable document summarizer. In Proceeding8 of the 18th Annual Int. A CM/SIGIR Conference on Research and Development in IR, pages 68-73, Seattle, WA, July 1995. Google Scholar
4.P.H. Luhn. Automatic creation of literature abstracts. IBM Journal, pages 159-165, 1958.Google ScholarDigital Library
5.G. Salton. Automatic Text Processing: The Transformation, Analysis, and Retrieval oJ Information by Computer. Addison-Wesley, 1989. Google ScholarDigital Library
6.In TIPSTER Text Phase 11I 18-Month Workshop, Fairfax, VA, May 1998.Google Scholar

Index Terms

The use of MMR, diversity-based reranking for reordering documents and producing summaries
Information systems

Data management systems

Database management system engines

Database query processing

Information retrieval

Evaluation of retrieval results

Relevance assessment

Information retrieval query processing

Theory of computation

Theory and algorithms for application domains

Database theory

Database query processing and optimization (theory)

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SIGIR ’98: Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
August 1998
394 pages
ISBN:1581130155
DOI:10.1145/290941
Chairmans:
W. Bruce Croft
Univ. of Massachusetts
,
Alistair Moffat
Univ. of Melbourne, Victoria, Australia
,
C. J. van Rijsbergen
Univ. of Glasgow, Scotland, UK
,
Ross Wilkinson
RMIT Univ., Australia and CSIRO
,
Justin Zobel
RMIT Univ., Australia

Copyright © 1998 ACM

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Association for Computing Machinery
New York, NY, United States

Publication History
Published: 1 August 1998

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