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Murtagh, F. – Information Processing and Management, 1984
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)
Descriptors: Algorithms, Cluster Analysis, Cluster Grouping, Data Analysis

Kamel, M.; And Others – Information Processing and Management, 1990
Discusses the problem of processing fuzzy queries in databases and information retrieval systems and presents a prototype of a fuzzy query processing system for databases that is based on data clustering and uses Pascal programing language. Clustering schemes are explained, and the system architecture that uses natural language is described. (14…
Descriptors: Algorithms, Cluster Grouping, Computer System Design, Databases

Rasmussen, Edie M.; And Others – Information Processing and Management, 1991
This issue contains nine articles that provide an overview of trends and research in parallel information retrieval. Topics discussed include network design for text searching; the Connection Machine System; PThomas, an adaptive information retrieval system on the Connection Machine; algorithms for document clustering; and system architecture for…
Descriptors: Algorithms, Cluster Grouping, Computer Networks, Computer System Design

Stanfel, Larry E. – Information Processing and Management, 1983
Describes methods for effecting the partition of information systems consisting of many components and interconnections into subsystems which are later made to interface with one another achieving an overall system. Clustering algorithms for the specific case of information systems are obtained and exemplified. Twenty-seven references are…
Descriptors: Algorithms, Cluster Analysis, Cluster Grouping, Design Requirements

Can, Fazli – Information Processing and Management, 1994
Discussion of relevancy in information retrieval systems focuses on an analysis of the efficiency of various cluster-based retrieval (CBR) strategies. A method for combining CBR and inverted index search is proposed that is cost effective in terms of time efficiency; and results of experiments are reported. (Contains 32 references.) (LRW)
Descriptors: Algorithms, Cluster Grouping, Comparative Analysis, Cost Effectiveness