In this paper, we present an agglomerative fuzzy K-Means clustering algorithm for numerical data, an extension to the standard fuzzy K-Means algorithm by introducing a penalty term...
Mark Junjie Li, Michael K. Ng, Yiu-ming Cheung, Jo...
Background: Gene clustering for annotating gene functions is one of the fundamental issues in bioinformatics. The best clustering solution is often regularized by multiple constra...
Jia Zeng, Shanfeng Zhu, Alan Wee-Chung Liew, Hong ...
Cluster ensembles provide a framework for combining multiple base clusterings of a dataset to generate a stable and robust consensus clustering. There are important variants of th...
We propose using large-scale clustering of dependency relations between verbs and multiword nouns (MNs) to construct a gazetteer for named entity recognition (NER). Since dependen...
Background: Conservation and variation scores are used when evaluating sites in a multiple sequence alignment, in order to identify residues critical for structure or function. A ...