K-Means clustering is widely used in information retrieval and data mining. Distributed K-Means variants have already been proposed, but none of the past algorithms scales to large...
Odysseas Papapetrou, Wolf Siberski, Fabian Leitrit...
Abstract. One solution to the lack of label problem is to exploit transfer learning, whereby one acquires knowledge from source-domains to improve the learning performance in the t...
Large amounts of remotely sensed data calls for data mining techniques to fully utilize their rich information content. In this paper, we study new means of discovery and summariz...
Predictive data mining typically relies on labeled data without exploiting a much larger amount of available unlabeled data. The goal of this paper is to show that using unlabeled...
Kang Peng, Slobodan Vucetic, Bo Han, Hongbo Xie, Z...
Main approaches to corpus-based semantic class mining include distributional similarity (DS) and pattern-based (PB). In this paper, we perform an empirical comparison of them, bas...