Using examples of data from the areas of information retrieval and of multivariate data analysis, six hierarchic clustering algorithms (single link, median, centroid, group average, complete link, Wards's) are examined and evaluated by using three proposed coefficients of hierarchic structure. Nine references are cited. (EJS)

Discussion of models for information retrieval focuses on an application of linear algebra to text clustering, namely, a metric for measuring cluster quality based on the theory that cluster quality is proportional to the number of terms that are disjoint across the clusters. Explains term-document matrices and clustering algorithms. (Author/LRW)

Develops a method of rough retrieval, an application of the rough set theory to information retrieval. The aim is to: (1) show that rough sets are naturally applied to information retrieval in which categorized information structure is used; and (2) show that a fuzzy retrieval scheme is induced from the rough retrieval. (AEF)

Discusses object-centered knowledge representation and information retrieval. Highlights include semantic networks; frames; predicative (declarative) and associative knowledge; cluster analysis; creation of subconcepts and superconcepts; automatic classification; hierarchies and pseudohierarchies; graph theory; term classification; clustering of…

Shows how to automatically construct a classification of users and a clustering of documents and cross-references among clusters based on users' information needs. Feedback in the construction of this classification and clustering that allows for the classification to be changed to reflect changing needs of users is also described. (22 references)…

Defines the notion of serial clustering of words in text, and explores the value of such clustering as an indicator of a word's bearing content. This approach is flexible in the sense that it is context-sensitive; a numerical approach may also be of value in assigning weights to terms in requests. Experimental support is obtained from natural text…

Reviews visualization techniques for scientific disciplines and information retrieval and classification. Highlights include historical background of scientometrics, bibliometrics, and citation analysis; map generation; process flow of visualizing knowledge domains; measures and similarity calculations; vector space model; factor analysis;…