This paper proposes a new clustering algorithm in the fuzzy-c-means family, which is designed to cluster time series and is particularly suited for short time series and those wit...
Abstract. Clustering is a problem of great practical importance in numerous applications. The problem of clustering becomes more challenging when the data is categorical, that is, ...
How to merge and organise query results retrieved from different resources is one of the key issues in distributed information retrieval. Some previous research and experiments su...
Recent research shows that ontology as background knowledge can improve document clustering quality with its concept hierarchy knowledge. Previous studies take term semantic simila...
Xiaodan Zhang, Liping Jing, Xiaohua Hu, Michael K....
We present a novel unsupervised learning scheme that simultaneously clusters variables of several types (e.g., documents, words and authors) based on pairwise interactions between...