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)

A measure for the quantification of the changes in classification under small changes in data is proposed. (Author)

Presents system for automatic handling of ordered sets, states based on these sets, and differing points of view regarding Universe of Discourse. Aspects are represented by new logical "overlap" function with examples taken from Ranganathan's horse and carriage parable and several books involving four main concepts (history, geography,…

Describes a cluster-based information retrieval procedure that can significantly reduce the computational requirements of the single linkage method, while still maintaining the retrieval effectiveness of the resulting classifications. Use of nearest neighbors, experimental details, and results and conclusions are highlighted. Fourteen references…

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…

Defines relationship between user profile and user query in terms of relationship between clusters of documents retrieved by each, and explores the expression of cluster similarity and cluster overlap as linear functions of similarity existing between original pairs of profiles and queries, given the desired retrieval threshold. (23 references)…

Introduces a novel approach to unsupervised text summarization. Proposes an "information-centric" approach to evaluation, where the quality of summaries is judged not in terms of how well they match human-created summaries but in terms of how well they represent their source documents in information retrieval tasks such as document…

Describes a study conducted on the cystic fibrosis (CF) database, a subset of MEDLINE, that investigated clustering structure and the effectiveness of cluster-based retrieval as a function of the exhaustivity of the uncontrolled subject descriptions. Results are compared to calculations for controlled descriptions based on Medical Subject Headings…

Reports on comparative study of document classifications produced by use of single linkage, complete linkage, group average, and Ward clustering methods. Findings of work that compares use of clusters consisting of pairs of documents with conventional best match searches are also reported. Thirty-four references are provided. (EJS)

Considers classifications produced by application of single linkage, complete linkage, group average, and word clustering methods to Keen and Cranfield document test collections, and studies structure of hierarchies produced, extent to which methods distort input similarity matrices during classification generation, and retrieval effectiveness…

This paper focuses on clustering a World Wide Web site (i.e., the 1998 World Cup Soccer site) into groups of documents that are predictive of future user accesses. Two approaches were developed and tested. The first approach uses semantic information inherent in the documents to facilitate the clustering process. User access history is then used…

Proposes use of parallel computing systems to overcome the computationally intense clustering process. Results show some near linear speed up in higher threshold clustering applications, meeting the requirements to classify, group and process large document sets within nonprohibitive execution times. Includes graphs and charts. (JAK)

This study attempts to analyze descriptors taken from subject categories in ERIC thesaurus and used as search terms on CROSS database Bibliographic Retrieval Services. An expectation ratio was computed and cluster analysis was conducted to discover subject relationships among databases. A list of databases retrieved and 12 references are appended.…

Describes method of automatic document classification in which documents classed as QA by Library of Congress classification system were clustered at six thresholds by keyword using single link technique. Automatically generated clusters were compared to Library of Congress subclasses, and partial classified hierarchy was formed. Twelve references…