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Peer reviewedZanger, Daniel Z. – Information Processing & Management, 2002
Presents an interpolation theorem for an extended Boolean information retrieval model. Results show that whenever two or more documents are similarly ranked at any two points for a query containing exactly two terms, then they are similarly ranked at all points in between; and that results can fail for queries with more than two terms. (Author/LRW)
Descriptors: Information Retrieval, Mathematical Formulas, Models
Peer reviewedLe Calve, Anne; Savoy, Jacques – Information Processing & Management, 2000
Presents a new model for combining multiple sources of evidence in database merging based on logistic regression, and occurring only when ranks are available as a key to be used to merge different ranked lists obtained by various retrieval schemes. Results indicate better retrieval effectiveness than other approaches. (LRW)
Descriptors: Databases, Information Retrieval, Mathematical Formulas, Models
Peer reviewedWu, Jian Kang; Narasimhalu, A. Desai – Information Processing & Management, 1998
Proposes a fuzzy-image database model and a concept of fuzzy space; describes fuzzy-query processing in fuzzy space and fuzzy indexing on complete fuzzy vectors; and uses an example image database, the computer-aided facial-image inference and retrieval system (CAFIIR), for explanation throughout. (Author/LRW)
Descriptors: Content Analysis, Databases, Indexing, Information Retrieval
Peer reviewedMiyamoto, Sadaaki – Information Processing & Management, 2003
Proposes a fuzzy multiset model for information clustering with application to information retrieval on the World Wide Web. Highlights include search engines; term clustering; document clustering; algorithms for calculating cluster centers; theoretical properties concerning clustering algorithms; and examples to show how the algorithms work.…
Descriptors: Algorithms, Information Retrieval, Mathematical Formulas, Models
Peer reviewedBoughanem, M.; Chrisment, C.; Soule-Dupuy, C. – Information Processing & Management, 1999
Presents a relevance-feedback strategy that improves the effectiveness of information-retrieval systems based on back-propagation of the relevance of retrieved documents using an algorithm developed in a neural approach. Describes a neural information-retrieval model and reports results obtained with the algorithm in three different environments.…
Descriptors: Algorithms, Information Retrieval, Mathematical Formulas, Models
Peer reviewedDominich, Sandor – Information Processing & Management, 2003
Discussion of connectionist views for adaptive clustering in information retrieval focuses on a connectionist clustering technique and activation spreading-based information retrieval model using the interaction information retrieval method. Presents theoretical as well as simulation results as regards computational complexity and includes…
Descriptors: Computation, Evaluation Methods, Information Retrieval, Interaction
Peer reviewedLosee, Robert M. – Information Processing & Management, 1997
Proposes a model for digital library and hypermedia organizations that is adaptive, providing different conceptual orderings to support browsing for different individuals' or groups' needs. Highlights include types of links, document ordering and the Gray code (a binary programming code), adaptive classification, and an economic model for document…
Descriptors: Classification, Documentation, Electronic Libraries, Hypermedia
Peer reviewedSyu, Inien; Lang, S. D. – Information Processing & Management, 2000
Explains how a competition-based connectionist model for diagnostic problem-solving is adapted to information retrieval. Topics include probabilistic causal networks; Bayesian networks; the neural network model; empirical studies of test collections that evaluated retrieval performance; precision results; and the use of a thesaurus to provide…
Descriptors: Competition, Evaluation Methods, Information Retrieval, Mathematical Formulas
Peer reviewedKang, Hyun-Kyu; Choi, Key-Sun – Information Processing & Management, 1997
Discussion of information retrieval and relevance focuses on mutual information, a measure which represents the relation between two words. A model of a natural-language information-retrieval system that is based on a two-level document-ranking method using mutual information is presented, and a Korean encyclopedia test collection is explained.…
Descriptors: Databases, Documentation, Encyclopedias, Foreign Countries
Peer reviewedStory, Roger E. – Information Processing & Management, 1996
Discussion of the use of Latent Semantic Indexing to determine relevancy in information retrieval focuses on statistical regression and Bayesian methods. Topics include keyword searching; a multiple regression model; how the regression model can aid search methods; and limitations of this approach, including complexity, linearity, and…
Descriptors: Algorithms, Difficulty Level, Indexing, Information Retrieval
Peer reviewedMoffat, Alistair; And Others – Information Processing & Management, 1994
Describes an approximate document ranking process that uses a compact array of in-memory, low-precision approximations for document length. Combined with another rule for reducing the memory required by partial similarity accumulators, the approximation heuristic allows the ranking of large document collections using less than one byte of memory…
Descriptors: Database Design, Database Management Systems, Full Text Databases, Information Retrieval


