The problem of time series classification has attracted great interest in the last decade. However current research assumes the existence of large amounts of labeled training data...
K-means is a widely used partitional clustering method. While there are considerable research efforts to characterize the key features of K-means clustering, further investigation...
Massive publicly available gene expression data consisting of different experimental conditions and microarray platforms introduce new challenges in data mining when integrating m...
Extracting sentiments from unstructured text has emerged as an important problem in many disciplines. An accurate method would enable us, for example, to mine online opinions from ...
Projected clustering has become a hot research topic due to its ability to cluster high-dimensional data. However, most existing projected clustering algorithms depend on some cri...