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Clark, C. V. – Journal of Documentation, 1976
Here the year by year issue of U.S. patents since 1836 is used to correct for growth their apparent aging, as obtained by a synchronous study of citations made by (a) U.S. patent examiners and (b) periodicals. Apparent and corrected aging are treated in terms of conditional probabilities. (Author)
Descriptors: Obsolescence, Probability, Statistical Analysis
Peer reviewed Peer reviewed
Robertson, S. E. – Journal of Documentation, 1977
The principle that, for optimal retrieval, documents should be ranked in order of the probability of relevance is discussed. (Author/KP)
Descriptors: Information Retrieval, Probability, Relevance (Information Retrieval)
Peer reviewed Peer reviewed
Burrell, Quentin L. – Journal of Documentation, 1988
Proposes a probabilistic mechanism to describe various forms of the Bradford phenomenon reported in bibliographic research. The inclusion of a time parameter in the model to allow predictions of dynamic systems is explained. (58 references) (CLB)
Descriptors: Bibliometrics, Mathematical Models, Prediction, Probability
Peer reviewed Peer reviewed
Salton, Gerald – Journal of Documentation, 1979
Examines the main mathematical approaches to information retrieval, including both algebraic and probabilistic models, and describes difficulties which impede formalization of information retrieval processes. A number of developments are covered where new theoretical understandings have directly led to improved retrieval techniques and operations.…
Descriptors: Algebra, Bibliographies, Information Retrieval, Mathematical Models
Peer reviewed Peer reviewed
Nelson, Michael J. – Journal of Documentation, 1989
Presents a probability model of the occurrence of index terms used to derive discrete distributions which are mixtures of Poisson and negative binomial distributions. These distributions give better fits than the simpler Zipf distribution, have the advantage of being more explanatory, and can incorporate a time parameter if necessary. (25…
Descriptors: Goodness of Fit, Mathematical Models, Probability, Statistical Distributions
Peer reviewed Peer reviewed
Robertson, S. E.; Harding, P. – Journal of Documentation, 1984
Presents adaptation of a probabilistic theoretical model previously used in relevance feedback for use in automatic indexing of documents (in the sense of imitating) human indexers. Methods for model application are proposed, independence assumptions used in the model are interpreted, and the probability of a dependence model is discussed.…
Descriptors: Automatic Indexing, Classification, Information Retrieval, Mathematical Models
Peer reviewed Peer reviewed
Robertson, Stephen; Walker, Stephen – Journal of Documentation, 2000
Discusses methods to be used in an adaptive filtering task, in which incoming documents are routed to users according to stored profiles. Highlights include decision thresholds to help in the retrieval decision; probability of relevance; calibration and logistic regression; feedback; and examples in the Okapi text retrieval system. (LRW)
Descriptors: Decision Making, Documentation, Feedback, Information Retrieval
Peer reviewed Peer reviewed
Radecki, Tadeusz – Journal of Documentation, 1982
Presents and discusses the results of research into similarity measures for search request formulations which employ Boolean combinations of index terms. The use of a weighting mechanism to indicate the importance of attributes in a search formulation is described. A 16-item reference list is included. (JL)
Descriptors: Information Retrieval, Mathematical Models, Measurement Techniques, Probability
Peer reviewed Peer reviewed
Croft, W. B.; Harper, D. J. – Journal of Documentation, 1979
Retrieval experiments with the Cranfield collection of 1,400 documents used strategies based on a probabilistic model for an initial search and intermediate search when no relevant documents were known. Results show initial strategy is better than conventional strategies in retrieval effectiveness and number of queries needed to retrieve…
Descriptors: Information Retrieval, Mathematical Models, Online Systems, Probability