Sachin Shinde
ABSTRACT
Clustering focuses to organize a collection of data items into clusters, such that items within a cluster are more "similar" to each other than they are to items in the other clusters. The k-means method is one of the most widely used clustering techniques for various applications. Applications like Searching, Retrieving as well as Reading research Documents are more Time consuming because we need more time for searching or reading single papers or document, so it is required that use enhanced search engine which is based on fastest reading algorithm which provides best output or results. So we are proposed Enhanced architecture with improved k-means algorithm, which proposes a method for making the algorithm more effective and efficient, so as to get better clustering with reduced complexity. It will search the base keyword or string of the content from the knowledge database. Proposed work uses the search engine based on clustering and text mining.
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Index Terms
- Knowledge Discovery for research Documents using Improved K-means Technique
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