Harmony K-means algorithm for document clustering

@article{Mahdavi2008HarmonyKA,
  title={Harmony K-means algorithm for document clustering},
  author={Mehrdad Mahdavi and Hassan Abolhassani},
  journal={Data Mining and Knowledge Discovery},
  year={2008},
  volume={18},
  pages={370-391}
}
Fast and high quality document clustering is a crucial task in organizing information, search engine results, enhancing web crawling, and information retrieval or filtering. Recent studies have shown that the most commonly used partition-based clustering algorithm, the K-means algorithm, is more suitable for large datasets. However, the K-means algorithm can generate a local optimal solution. In this paper we propose a novel Harmony K-means Algorithm (HKA) that deals with document clustering… CONTINUE READING
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