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Ouvrages Année : 2015

Diagonal Co-clustering Algorithm for Document-Word Partitioning

Charlotte Laclau
Mohamed Nadif

Résumé

We propose a novel diagonal co-clustering algorithm built upon the double Kmeans to address the problem of document-word co-clustering. At each iteration, the proposed algorithm seeks for a diagonal block structure of the data by minimizing a criterion based on the variance within and the centroid effect. In addition to be easy-to-interpret and efficient on sparse binary and continuous data, Diagonal Double Kmeans (DDKM) is also faster than other state-of-the art clustering algorithms. We illustrate our contribution using real datasets commonly used in document clustering.
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Dates et versions

hal-01224170 , version 1 (04-11-2015)

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Citer

Charlotte Laclau, Mohamed Nadif (Dir.). Diagonal Co-clustering Algorithm for Document-Word Partitioning. pp.170-180, 2015, Advances in Intelligent Data Analysis {XIV}, ⟨10.1007/978-3-319-24465-5_15⟩. ⟨hal-01224170⟩

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