Efficient Clustering Technique for Information Retrieval in Data Mining

Abstract

In the emerging new wave of applications where people are the ultimate target of text clustering methods, cluster labels are intended to be read and comprehended by humans. The primary objective of a clustering method should be to focus on providing good, descriptive cluster labels in addition to optimizing traditional clustering quality indicators such as document-togroup assignment. In yet other words: in document browsing, text clustering serves the main purpose of describing and summarizing a larger set of documents; the particular document assignment is of lesser importance. Descriptive clustering is a problem of discovering diverse groups of semantically related documents described with meaningful, comprehensible and compact text labels. In this paper a new type of clustering methods for information retrieval which focuses on revealing the structure of document collections is discussed, summarizing their content and presenting this content to a human user in a compact way.

Authors and Affiliations

Anjali D. Raut, Prof. Prajakta. P. Chapke

Keywords

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  • EP ID EP21809
  • DOI -
  • Views 227
  • Downloads 5

How To Cite

Anjali D. Raut, Prof. Prajakta. P. Chapke (2016). Efficient Clustering Technique for Information Retrieval in Data Mining. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 4(3), -. https://europub.co.uk/articles/-A-21809