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Negoita, C. V. – International Journal of Man-Machine Studies, 1976
The IR systems are faced with a need to manage fuzziness and not merely to react to fuzziness. Fuzzy set theory can be used to model the indexing and retrieval processes. (BD)
Descriptors: Indexing, Mathematical Models, Relevance (Information Retrieval), Search Strategies

Buell, Duncan A.; Kraft, Donald H. – Journal of the American Society for Information Science, 1981
Analyzes the nature of Boolean information retrieval in relation to the discrete weights of query terms, examines assigned weights from an approach involving thresholds, and generates an evaluation mechanism which allows the user to attach a threshold to the query term. Thirteen references are listed. (FM)
Descriptors: Bibliographies, Evaluation Methods, Indexing, Information Retrieval

Kwok, K. L. – Journal of the American Society for Information Science, 1985
Introduces a new model of viewing documents based on citing-cited relationship between them. Using Bayes' decision theory, it is shown how source document may be indexed and weighted by relevant cited document features, corresponding to one pass relevance feedback Model 1 (probabilistic indexing) or Model 2 (probabilistic retrieval). (24…
Descriptors: Citations (References), Feedback, Indexing, Information Retrieval

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
De Heer, T. – Information Storage and Retrieval, 1974
Use of syntactic trace as an access strategy for large files containing arbitrary languages for which thesaurus-based and multiple attribute search techniques are unsuitable. (LS)
Descriptors: Indexing, Information Retrieval, Information Storage, Mathematical Models
Yu, C. T.; Salton, G. – 1975
Formal proofs are given of the effectiveness under well-defined conditions of the thesaurus method in information retrieval. It is shown, in particular, that when certain semantically related terms are added to the information queries originally submitted by the user population, a superior retrieval system is obtained in the sense that for every…
Descriptors: Automatic Indexing, Information Retrieval, Information Storage, Mathematical Models

Biru, Tesfaye; And Others – Journal of Documentation, 1989
Discusses the effect of including relevance data on the calculation of term discrimination values in bibliographic databases. Algorithms that calculate the ability of index terms to discriminate between relevant and non-relevant documents are described and tested. The results are discussed in terms of the relationship between term frequency and…
Descriptors: Algorithms, Automatic Indexing, Bibliographic Databases, Mathematical Models

Fuhr, Norbert – Information Processing and Management, 1989
Describes three models for probabilistic indexing, all based on the Darmstadt automatic indexing approach, and presents experimental evaluation results for each. The discussion covers the improved retrieval effectiveness of probabilistic indexing over binary indexing, and suggestions for using this automatic indexing method with free text terms.…
Descriptors: Automatic Indexing, Comparative Analysis, Information Retrieval, Mathematical Formulas

Deerwester, Scott; And Others – Journal of the American Society for Information Science, 1990
Describes a new method for automatic indexing and retrieval called latent semantic indexing (LSI). Problems with matching query words with document words in term-based information retrieval systems are discussed, semantic structure is examined, singular value decomposition (SVD) is explained, and the mathematics underlying the SVD model is…
Descriptors: Automatic Indexing, Documentation, Factor Analysis, Information Retrieval

Salton, Gerard; Buckley, Christopher – Information Processing and Management, 1988
Summarizes the experimental evidence that indicates that text indexing systems based on the assignment of appropriately weighted single terms produce retrieval results superior to those obtained with more elaborate text representations, and provides baseline single term indexing models with which more elaborate content analysis procedures can be…
Descriptors: Automatic Indexing, Comparative Analysis, Content Analysis, Information Retrieval

Parker, Lorraine M. Purgailis – Journal of the American Society for Information Science, 1983
The mathematical model proposed describes a computerized bibliographic information system which includes a method--document learning--of improving the set of index terms assigned to a document representative. Inputs to the information system (index terms and query), relevance feedback, and assumptions concerning the model are discussed.…
Descriptors: Automation, Databases, Indexing, Information Needs

Bordogna, G; And Others – Information Processing and Management, 1991
Presents an analytical approach to the interpretation of weighted Boolean queries. By distinguishing query term weights from query weights, a query becomes a means of describing classes of ideal documents and expressing relativity criteria among these descriptions. A formalization of query term weights is given in a fuzzy set theoretical context.…
Descriptors: Evaluation Criteria, Indexing, Information Retrieval, Information Science

Losee, Robert M. – Information Processing and Management, 1991
Provides a method for estimating precision without examining individual database documents, which requires knowledge of only the query or expressed information need and a set of database parameters constant for all queries. Concepts of historic and expected precision are examined, and applications of precision-document graphs are assessed. (36…
Descriptors: Evaluation Criteria, Expert Systems, Hypermedia, Indexing