Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
An automated knowledge extraction system
An automated knowledge extraction system
Fuzzy sets and their application to clustering and training
Fuzzy sets and their application to clustering and training
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
A matrix density based algorithm to hierarchically co-cluster documents and words
WWW '03 Proceedings of the 12th international conference on World Wide Web
Information-theoretic co-clustering
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Restrictive clustering and metaclustering for self-organizing document collections
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Biclustering Algorithms for Biological Data Analysis: A Survey
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
General C-Means Clustering Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Co-clustering by block value decomposition
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
A partitioning based algorithm to fuzzy co-cluster documents and words
Pattern Recognition Letters
Document clustering with prior knowledge
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Feature diversity in cluster ensembles for robust document clustering
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Orthogonal nonnegative matrix t-factorizations for clustering
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
The possibilistic C-means algorithm: insights and recommendations
IEEE Transactions on Fuzzy Systems
Comments on “A possibilistic approach to clustering”
IEEE Transactions on Fuzzy Systems
Improved possibilistic C-means clustering algorithms
IEEE Transactions on Fuzzy Systems
A Possibilistic Fuzzy c-Means Clustering Algorithm
IEEE Transactions on Fuzzy Systems
Fuzzy clustering with weighted medoids for relational data
Pattern Recognition
Fuzzy relational clustering around medoids: A unified view
Fuzzy Sets and Systems
A possibilistic clustering approach toward generative mixture models
Pattern Recognition
International Journal of Intelligent Systems
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In this paper, we develop a new soft model dual fuzzy-possibilistic coclustering (DFPC) for document categorization. The proposed model targets robustness to outliers and richer representations of coclusters. DFPC is inspired by an existing algorithm called possibilistic fuzzy C-means (PFCM) that hybridizes fuzzy and possibilistic clustering. It has been shown that PFCM can perform effectively for low-dimensional data clustering. To achieve our goal, we expand this existing idea by introducing a novel PFCM-like coclustering model. The new algorithm DFPC preserves the desired properties of PFCM. In addition, as a coclustering algorithm, DFPC is more suitable for our intended high-dimensional application: document clustering. Besides, the coclustering mechanism enables DFPC to generate, together with document clusters, fuzzy-possibilistic word memberships. These word memberships, which are absent in the existing PFCM model, can play an important role in generating useful descriptions of document clusters. We detail the formulation of the proposed model and provide an extensive analytical study of the algorithm DFPC. Experiments on an artificial dataset and various benchmark document datasets demonstrate the effectiveness and potential of DFPC.