Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/TFUZZ.2008.924332 | IEEE T. Fuzzy Systems |
Keywords | Field | DocType |
document clustering,novel pfcm-like coclustering model,various benchmark document datasets,new soft model,document cluster,algorithm dfpc,proposed model targets robustness,dual fuzzy-possibilistic,document categorization,existing pfcm model,data clustering,coclustering,robustness,text mining,fuzzy set theory,possibility theory,fuzzy clustering,clustering algorithms,co clustering,information retrieval,classification,algorithm design and analysis | Fuzzy clustering,Data mining,Algorithm design,Document clustering,Fuzzy logic,Fuzzy set,Possibility theory,Artificial intelligence,Biclustering,Cluster analysis,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
17 | 3 | 1063-6706 |
Citations | PageRank | References |
13 | 0.65 | 20 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| William-Chandra Tjhi | 1 | 156 | 10.09 |
| Lihui Chen | 2 | 380 | 27.30 |