Semi-supervised fuzzy co-clustering algorithm for document categorization

  title={Semi-supervised fuzzy co-clustering algorithm for document categorization},
  author={Yang Yan and Lihui Chen and William-Chandra Tjhi},
  journal={Knowledge and Information Systems},
In this paper, we propose a new semi-supervised fuzzy co-clustering algorithm called SS-FCC for categorization of large web documents. In this new approach, the clustering process is carried out by incorporating some prior domain knowledge of a dataset in the form of pairwise constraints provided by users into the fuzzy co-clustering framework. With the help of those constraints, the clustering problem is formulated as the problem of maximizing a competitive agglomeration cost function with… CONTINUE READING


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Publications referenced by this paper.
Showing 1-10 of 52 references

Non-negative matrix factorization for semi-supervised data clustering

Knowledge and Information Systems • 2008
View 9 Excerpts
Highly Influenced

Active semi-supervised fuzzy clustering

Pattern Recognition • 2008
View 4 Excerpts
Highly Influenced

Efficient online spherical k-means clustering

Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005. • 2005
View 5 Excerpts
Highly Influenced

Composite kernels for semi-supervised clustering

Knowledge and Information Systems • 2010
View 1 Excerpt

Semi-Supervised Nonnegative Matrix Factorization

IEEE Signal Processing Letters • 2010
View 1 Excerpt

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