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Harter, Stephen P. – Journal of the American Society for Information Science, 1975
Confirms previously published research in concluding that specialty words tend to possess frequency distributions which cannot be described by a single Poisson distribution. (Author/PF)
Descriptors: Automatic Indexing, Indexing, Keywords, Mathematical Models

Bookstein, Abraham; Swanson, Don R. – Journal of the American Society for Information Science, 1974
Descriptors: Automatic Indexing, Cluster Grouping, Indexes, Information Retrieval

Melucci, Massimo – Information Retrieval, 1999
Assesses the retrieval effectiveness of automatically constructed interdocument hypertext links in information retrieval (IR). Describes experiments using statistical and probabilistic techniques that were designed to obtain evidence concerning the usefulness of querying and browsing automatically constructed IR hypertexts. Results indicate a…
Descriptors: Automatic Indexing, Hypermedia, Information Retrieval, Probability

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

White, Lee J.; And Others – 1975
The major advantage of sequential classification, a technique for automatically classifying documents into previously selected categories, is that the entire document need not be processed before it is classified. This method assumes the availability of a priori categories, a selection of keywords representative of these categories, and the a…
Descriptors: Algorithms, Automatic Indexing, Bayesian Statistics, Classification

Silva, Wagner Teixeira da; Milidiu, Ruy Luiz – Journal of the American Society for Information Science, 1993
Describes the Belief Function Model for automatic indexing and ranking of documents which is based on a controlled vocabulary and on term frequencies in each document. Belief Function Theory is explained, and the Belief Function Model is compared to the Standard Vector Space Model. (17 references) (LRW)
Descriptors: Automatic Indexing, Comparative Analysis, Documentation, Information Retrieval
Feldman, Susan – Searcher, 2000
Discusses information retrieval systems and the need to have them adapt to user needs, integrate information in any format, reveal patterns and trends in information, and answer questions. Topics include statistics and probability; natural language processing; intelligent agents; concept mapping; machine-aided indexing; text mining; filtering;…
Descriptors: Automatic Indexing, Concept Mapping, Information Retrieval, Information Systems
Kar, B. Gautam; White, Lee J. – 1975
The feasibility of using a distance measure, called the Bayesian distance, for automatic sequential document classification was studied. Results indicate that, by observing the variation of this distance measure as keywords are extracted sequentially from a document, the occurrence of noisy keywords may be detected. This property of the distance…
Descriptors: Algorithms, Automatic Indexing, Bayesian Statistics, Classification

Damerau, Fred J. – Information Processing and Management, 1993
Examines the use of various statistical techniques for generating domain-oriented multiword vocabulary terms for natural language database systems. Conclusions show the vocabulary clustering effect should be considered when making significance calculations and that a simple ratio of subject matter relative frequency to total sample relative…
Descriptors: Automatic Indexing, Cluster Analysis, Comparative Analysis, Database Design