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Robertson, Alexander M.; Willett, Peter – Journal of Documentation, 1996
Describes a genetic algorithm (GA) that assigns weights to query terms in a ranked-output document retrieval system. Experiments showed the GA often found weights slightly superior to those produced by deterministic weighting (F4). Many times, however, the two methods gave the same results and sometimes the F4 results were superior, indicating…
Descriptors: Algorithms, Comparative Analysis, Information Retrieval, Online Searching
Peer reviewed Peer reviewed
Gordon, Michael D. – Information Processing and Management, 1991
Presents a theoretical rationale for employing a form of information retrieval algorithm that helps searchers better navigate through large document collections by continually revising probability estimates for document subsets. The algorithm avoids assumptions of index term independence and predicts relevance more accurately with increasing…
Descriptors: Algorithms, Feedback, Indexing, Information Needs
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Carroll, David M.; And Others – Journal of the American Society for Information Science, 1988
Describes the use of a highly parallel array processor for pattern matching operations in a bibliographic retrieval system. The discussion covers the hardware and software features of the processor, the pattern matching algorithm used, and the results of experimental tests of the system. (37 references) (Author/CLB)
Descriptors: Algorithms, Automatic Indexing, Bibliographic Databases, Computational Linguistics
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Willett, Peter – Information Processing and Management, 1985
Reports algorithm for calculation of term discrimination values that is sufficiently fast in operation to permit use of exact values. Evidence is presented to show that relationship between term discrimination and term frequency is crucially dependent upon type of inter-document similarity measure used for calculation of discrimination values. (13…
Descriptors: Algorithms, Graphs, Information Retrieval, Information Systems
Peer reviewed Peer reviewed
Smith, F. J.; Devine, K. – Information Processing and Management, 1985
Zipfian laws for frequency distributions of word pairs and longer phrases are derived from text sample analysis. From crossing of Zipfian curves, it is deduced that number of multi-word phrases that occur frequently in text is surprisingly small, of same order of magnitude as number of individual word-types. (8 references) (EJS)
Descriptors: Algorithms, Graphs, Indexing, Information Retrieval