This preview shows page 1. Sign up to view the full content.
Unformatted text preview: ield excellent results. Hofmann (2001) formulates a variant that is able to cluster terms occurring together
instead of documents.
3.2.3 Alternative Clustering Approaches algorithm designate the simultaneous clustering of documents
and terms (Dhillon et al. 2003). They follow thereby another paradigm than
the "classical" cluster algorithm as KMeans which only clusters elements of the
Co-clustering 44 LDV-FORUM A Brief Survey of Text Mining
one dimension on the basis of their similarity to the second one, e.g. documents
based on terms.
While most classical clustering algorithms assign each datum
to exactly one cluster, thus forming a crisp partition of the given data, fuzzy
clustering allows for degrees of membership, to which a datum belongs to different
clusters (Bezdek 1981). These approaches are frequently more stable. Applications to text are described in, e.g., Mendes & Sacks (2001); Borgelt & Nürnberger
Fuzzy Clustering We have described the most important types of clusteri...
View Full Document
- Summer '11