An Efficient Similarity Based Measures-Fix up Using Heuristic Scheduling
Abstract- A similarity or distance measures two data points is a core requirement for several data mining and knowledge discovery tasks. To identify the similarity measures by using classification and clustering. A Large set of text documents are increasingly common. To identify a suitable algorithm for clustering that produces the best clustering solutions it becomes necessary to have a method for comparing the results of different clustering algorithms. Using words as features, text documents are often represented as high-dimensional vectors. The effectiveness of measures is evaluated on several real-world data sets like customer reviews for text classification and Clustering problems. The result shows that the performance obtained by the proposed measure is better than that achieved by other measures. The final result using for the heuristic Scheduling Algorithm, it?s a new scheduling algorithm to arrange and distribute the already clustered data through this scheduler, now all clusters are efficiently and accurately distribute to needed users.
Index Terms –SimilarityMeasures, Classifiers, DocumentClustering, Text Classification, HeuristicScheduling
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International Journal for Trends in Technology & Engineering © 2015 IJTET JOURNAL