Hybridization of K-means and Harmony Search Method for Text Clustering Using Concept Factorization

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Provided by: International Journal of Advanced Research in Computer Engineering & Technology
Topic: Data Management
Format: PDF
Huge amount of heterogeneous information is available on the web. Clustering is one of the techniques to deal with enormous amount of information. Clustering partitions a data set into groups where data objects in each group should exhibit large degree of similarity. Data objects with high similarity measure should be placed in a cluster (intra cluster). Similarity between the data objects of different clusters should be less (inter cluster). The frequently used partitioning-based clustering algorithm is K-means algorithm. K-means algorithm is simple, straightforward, easy to implement and works efficiently in many applications.
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