Discretization algorithms have played an important role in data mining and knowledge discovery. They not only produce a concise summarization of continuous attributes to help the ...
One of the most utilized data mining tasks is the search for association rules. Association rules represent significant relationships between items in transactions. We extend the...
Oliver Schulte, Flavia Moser, Martin Ester, Zhiyon...
A methodology for automatically identifying and clustering semantic features or topics in a heterogeneous text collection is presented. Textual data is encoded using a low rank no...
Farial Shahnaz, Michael W. Berry, V. Paul Pauca, R...
Abstract Relational rule learning algorithms are typically designed to construct classification and prediction rules. However, relational rule learning can be adapted also to subgr...
article we investigate an attribute-oriented induction approach for acquisition of abstract knowledge from data stored in a fuzzy database environment. We utilize a proximity-based...