@inproceedings{d1257dc0422e488ea0c1e20bffd1a9bf,
title = "Diagonal co-clustering algorithm for document-word partitioning",
abstract = "We propose a novel diagonal co-clustering algorithm built upon the double Kmeans to address the problem of document-word coclustering. 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.",
author = "Charlotte Laclau and Mohamed Nadif",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 14th International Symposium on Intelligent Data Analysis, IDA 2015 ; Conference date: 22-10-2015 Through 24-10-2015",
year = "2015",
month = jan,
day = "1",
doi = "10.1007/978-3-319-24465-5\_15",
language = "English",
isbn = "9783319244648",
series = "Lecture Notes in Computer Science",
publisher = "Springer Verlag",
pages = "170--180",
editor = "Elisa Fromont and \{De Bie\}, Tijl and \{van Leeuwen\}, Matthijs",
booktitle = "Advances in Intelligent Data Analysis XIV - 14th International Symposium, IDA 2015, Proceedings",
}