Mining frequent itemsets is a popular method for finding associated items in databases. For this method, support, the co-occurrence frequency of the items which form an associatio...
We show how global constraints such as transitivity can be treated intensionally in a Zero-One Integer Linear Programming (ILP) framework which is geared to find the optimal and c...
We present a novel approach for multilingual document clustering using only comparable corpora to achieve cross-lingual semantic interoperability. The method models document colle...
With the growing importance of time series clustering research, particularly for similarity searches amongst long time series such as those arising in medicine or finance, it is cr...
Background: Mean-based clustering algorithms such as bisecting k-means generally lack robustness. Although componentwise median is a more robust alternative, it can be a poor cent...
Yuanyuan Ding, Xin Dang, Hanxiang Peng, Dawn Wilki...