Clustering is an essential data mining task with numerous applications. However, data in most real-life applications are high-dimensional in nature, and the related information of...
Recently, there has been an increased interest in "lifelong" machine learning methods, that transfer knowledge across multiple learning tasks. Such methods have repeated...
Large, dynamic, and ad-hoc organizations must frequently initiate data integration and sharing efforts with insufficient awareness of how organizational data sources are related. ...
Ken Smith, Craig Bonaceto, Chris Wolf, Beth Yost, ...
—In the past, we proposed a genetic-fuzzy data-mining algorithm for extracting both association rules and membership functions from quantitative transactions under a single minim...
Chun-Hao Chen, Tzung-Pei Hong, Vincent S. Tseng, C...
In modern clustering environments where the memory hierarchy has many layers (distributed memory, shared memory layer, cache, ¡ ¢ ), an important question is how to fully u...