Concepts of the cover coefficient-based clustering methodology

Abstract

Document clustering has several unresolved, problems. Among them, are high time and space complexity, difficulty af determining similarity thresholds, order dependence, nonuniform, document distribution in clusters, and arbitrariness in determination of various cluster initiators. To overcome these problems to some degree, the cover coefficient based clustering methodology has been introduced. The concepts used in this methodology have created certain new concepts, relationships, and measures such as the effect of indexing on clustering, an optimal vocabulary generation for indexing, and a new matching function. These new concepts are discussed. The result of performance experiments that show the effectiveness of the clustering methodology and the matching function are also included. In these experiments, it has been also observed that the majority of the documents obtained in a search are concentrated in a few clusters containing a low percentage of documents of the database.