Noble Approach for Documents Clustering Using Semantics Relations and K-means Algorithm

Computer Science

Fast and high-quality document clustering algorithms play an important role in effectively navigating, summarizing, and organizing information. Recent studies have shown that partitional clustering algorithms are more suitable for clustering large datasets. However, the K-means algorithm, the most commonly used partitional clustering algorithm, can only generate a local optimal solution. In this research work, we present the k-means clustering algorithm with semantic wordnet to perform a globalized search in the entire solution space. We also used the semantic relations of dataset using wordnet. The proposed method can support the efficient clustering approach for document clustering.

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