Fuzzy clustering of web documents using equivalence relations and fuzzy hierarchical clustering
This addresses the challenge of handling uncertain natural data in web document clustering, but appears to be an incremental improvement on existing fuzzy clustering methods.
The authors tackled the problem of clustering web documents with vague and uncertain boundaries by developing a fuzzy clustering algorithm using equivalence relations and fuzzy hierarchical clustering, though no concrete performance numbers were provided in the abstract.
The conventional clustering algorithms have difficulties in handling the challenges posed by the collection of natural data which is often vague and uncertain. Fuzzy clustering methods have the potential to manage such situations efficiently. Fuzzy clustering method is offered to construct clusters with uncertain boundaries and allows that one object belongs to one or more clusters with some membership degree. In this paper, an algorithm and experimental results are presented for fuzzy clustering of web documents using equivalence relations and fuzzy hierarchical clustering.