A generalized binary probabilistic independence model

The main objective of this article is to develop a theoretical model for information retrieval. By utilizing more complete statistical information, a generalized binary probabilistic independence model is proposed. Earlier probabilistic independence models are shown to be special cases of the new mo...

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Bibliographic Details
Published in:Journal of the American Society for Information Science 1990-07, Vol.41 (5), p.324-329
Main Authors: Wong, S. K. M., Yao, Y. Y.
Format: Article
Language:English
Subjects:
Binary Vectors
Discriminant Analysis
Documentation
Exact sciences and technology
Fuzzy sets
Information and communication sciences
Information Retrieval
Information science. Documentation
Library and information science. General aspects
Mathematical Models
Probabilistic Models
Probability
Queries
R&D
Relevance (Information Retrieval)
Relevance feedback
Research & development
Research Needs
Retrieval performance measures
Sciences and techniques of general use
Statistical analysis
Theoretical Analysis
Theories, definitions and sources in information science
User Satisfaction (Information)
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Summary:The main objective of this article is to develop a theoretical model for information retrieval. By utilizing more complete statistical information, a generalized binary probabilistic independence model is proposed. Earlier probabilistic independence models are shown to be special cases of the new model. A quadratic discriminant function is obtained, which can be reduced to the linear discriminant functions of the conventional probabilistic models. © 1990 John Wiley & Sons, Inc.
ISSN:0002-8231
1097-4571
DOI:10.1002/(SICI)1097-4571(199007)41:5<324::AID-ASI2>3.0.CO;2-9