Concept learning in content-based image retrieval (CBIR) systems is a challenging task. This paper presents an active concept learning approach based on mixture model to deal with...
The ability to aggregate huge volumes of queries over a large population of users allows search engines to build precise models for a variety of query-assistance features such as ...
The issues of schema evolution and temporal object models are generally considered to be orthogonal and are handled independently. However, to properly model applications that nee...
Iqbal A. Goralwalla, Duane Szafron, M. Tamer Ö...
We present a deductive data model for concept-based query expansion. It is based abstraction levels: the conceptual, the expression and the occurrence level. Concepts and their re...
Modern enterprise applications are forced to deal with unreliable, inconsistent and imprecise information. Probabilistic databases can model such data naturally, but SQL query eva...