Article

Query expansion based on predictive algorithms for collaborative filtering

Authors:

Keiichiro Hoashi,

Kazunori Matsumoto,

Naomi Inoue,

Kazuo HashimotoAuthors Info & Claims

SIGIR '01: Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval

Pages 414 - 415

https://doi.org/10.1145/383952.384063

Published: 01 September 2001 Publication History

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Abstract

No abstract available.

References

[1]

Rocchio: Relevance feedback in information retrieval. in SMART retrieval system - Experiments in automatic document processing, Prentice Hall Inc, pp 313-323, 1971.

Google Scholar

[2]

Breese, Heckerman, and Kadie: Empirical analysis of predictive algorithms for collaborative filtering. Proc of 14 th Conf of Uncertainty in Artificial Intelligence, pp 43-52, 1998.

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Google Scholar

[3]

Voorhees, Harman: The 6 th Text Retrieval Conference, NIST SP 500-240, 1998.

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Cited By

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Song YKołcz AGiles C(2009)Better Naive Bayes classification for high‐precision spam detectionSoftware: Practice and Experience10.1002/spe.92539:11(1003-1024)Online publication date: 22-Apr-2009
https://doi.org/10.1002/spe.925
Shapira BTaieb‐Maimon MNemeth Y(2005)Subjective and objective evaluation of interactive and automatic query expansionOnline Information Review10.1108/1468452051061782029:4(374-390)Online publication date: Aug-2005
https://doi.org/10.1108/14684520510617820

Index Terms

Query expansion based on predictive algorithms for collaborative filtering
1. Information systems
  1. Data management systems
    1. Database management system engines
      1. Database query processing
  2. Information retrieval
2. Theory of computation
  1. Theory and algorithms for application domains
    1. Database theory
      1. Database query processing and optimization (theory)

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Published In

SIGIR '01: Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval

September 2001

454 pages

ISBN:1581133316

DOI:10.1145/383952

Chairmen:
Donald H. Kraft
Louisiana State Univ.
,
W. Bruce Croft
University of Massachusetts, (For the Americas)
,
David J. Harper
The Robert Gordon University, (For Europe and Africa)
,
Justin Zobel
RMIT University, (For Asia and Australasia)

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 September 2001

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SIGIR

SIGIR01: 24th ACM/SIGIR International Conference on Research and Development in Information Retrieval

Louisiana, New Orleans, USA

Acceptance Rates

SIGIR '01 Paper Acceptance Rate 47 of 201 submissions, 23%;

Overall Acceptance Rate 792 of 3,983 submissions, 20%

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Cited By

View all

Song YKołcz AGiles C(2009)Better Naive Bayes classification for high‐precision spam detectionSoftware: Practice and Experience10.1002/spe.92539:11(1003-1024)Online publication date: 22-Apr-2009
https://doi.org/10.1002/spe.925
Shapira BTaieb‐Maimon MNemeth Y(2005)Subjective and objective evaluation of interactive and automatic query expansionOnline Information Review10.1108/1468452051061782029:4(374-390)Online publication date: Aug-2005
https://doi.org/10.1108/14684520510617820

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Recommendations

A hybrid approach for improving predictive accuracy of collaborative filtering algorithms

Typicality-Based Collaborative Filtering Recommendation

Trust-based collaborative filtering: tackling the cold start problem using regular equivalence