An important issue in text mining is how to make use of multiple pieces knowledge discovered to improve future decisions. In this paper, we propose a new approach to combining mult...
Traditional bag-of-words model and recent wordsequence kernel are two well-known techniques in the field of text categorization. Bag-of-words representation neglects the word orde...
Lei Zhang, Debbie Zhang, Simeon J. Simoff, John K....
In traditional data clustering, similarity of a cluster of objects is measured by pairwise similarity of objects in that cluster. We argue that such measures are not appropriate f...
Clustering time-series data poses problems, which do not exist in traditional clustering in Euclidean space. Specifically, cluster prototype needs to be calculated, where common s...
Spatial clustering is an important topic in knowledge discovery research. However, most clustering methods do not consider semantic information during the clustering process. In th...