Scholarly Commons

An electronic repository for the intellectual products of the Miami University community

Concepts and Effectiveness of the Cover Coefficient Based Clustering Methodology for Text Databases

DSpace/Manakin Repository

Show simple item record

dc.contributor.author Can, Fazli en_US
dc.contributor.author Ozkarahan, Esen en_US
dc.date.accessioned 2008-07-22T19:31:41Z en_US
dc.date.accessioned 2013-07-10T15:06:34Z
dc.date.available 2008-07-22T19:31:41Z en_US
dc.date.available 2013-07-10T15:06:34Z
dc.date.issued 1987-12-01 en_US
dc.date.submitted 2008-03-17 en_US
dc.identifier.uri
dc.identifier.uri http://hdl.handle.net/2374.MIA/246 en_US
dc.description.abstract An algorithm for document clustering is introduced. The base concept of the algorithm, Cover Coefficient (CC) concept, provides means of estimating the number of clusters within a document database. The CC concept is used also to identify the cluster seeds, to form clusters with the seeds, and to calculate Term Discrimination and Document Significance values (TDV, DSV). TDVs and DSVs are used to optimize document descriptions. The CC concept also relates indexing and clustering analytically. Experimental results indicate that the clustering performance in terms of the percentage of useful information accessed (precision) is forty percent higher, with accompanying reduction in search space, than that of random assignment of documents to clusters. The experiments have validated the indexing-clustering relationships and shown improvements in retrieval precision when TDV and DSV optimizations are used. en_US
dc.title Concepts and Effectiveness of the Cover Coefficient Based Clustering Methodology for Text Databases en_US
dc.type Text en_US
dc.type.genre Report en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search SC


Advanced Search

Browse

My Account