Descriptor
| Hypermedia | 4 |
| Mathematical Formulas | 4 |
| Algorithms | 2 |
| Indexing | 2 |
| Information Retrieval | 2 |
| Models | 2 |
| User Needs (Information) | 2 |
| Citation Indexes | 1 |
| Classification | 1 |
| Cluster Grouping | 1 |
| Comparative Analysis | 1 |
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| Information Processing &… | 1 |
| Information Systems | 1 |
| Journal of the American… | 1 |
| Online & CD-ROM Review | 1 |
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| Journal Articles | 4 |
| Reports - Descriptive | 4 |
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Peer reviewedShapira, Bracha; And Others – Online & CD-ROM Review, 1996
Discussion of hypertext browsing proposes a filtering algorithm which restricts the amount of information made available to the user by calculating the set of most relevant hypertext nodes for the user, utilizing the user profile and data clustering technique. An example is provided of an optimal cluster of relevant data items. (Author/LRW)
Descriptors: Algorithms, Hypermedia, Information Retrieval, Mathematical Formulas
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 reviewedSavoy, Jacques – Journal of the American Society for Information Science, 1997
Suggests a new ranking scheme especially adapted for hypertext environments in order to produce more effective retrieval results and still use Boolean search strategies. Topics include Boolean ranking schemes; single-term indexing and term weighting; fuzzy set theory extension; and citation indexing. (64 references) (Author/LRW)
Descriptors: Citation Indexes, Hypermedia, Indexing, Information Retrieval
Peer reviewedJohnson, Andrew; Fotouhi, Farshad – Information Systems, 1996
Discussion of hypermedia systems focuses on a comparison of two types of adaptive algorithm (genetic algorithm and neural network) in clustering hypermedia documents. These clusters allow the user to index into the nodes to find needed information more quickly, since clustering is "personalized" based on the user's paths rather than…
Descriptors: Algorithms, Cluster Grouping, Comparative Analysis, Electronic Text


