Most previous work on multiple models has been done on a few domains. We present a
comparsion of three ways of learning multiple models on 29 data sets from the UCI …

For learning tasks with few examples, greater classification accuracy can be achieved by
learning several concept descriptions for each class in the data and producing a …

In this paper we develop a mathematical analysis, based on empirical measurements, of
expected average improvements when integrating Machine Learning and Knowledge …

The paper addresses a problem of combining XML querying with ontology reasoning. We
present an extension of a rule-based XML query and transformation language Xcerpt. The …

For discrete optimization, the two basic search principles prevailing are stochastic local
search and population based search. Local search has difficulties to get out of local optima …

A general schema for integrating multiple reasoning systems is presented, along with its
implementation for emulsion quality control in the Sendzimir rolling mill. In this, probably the …

In this paper we address the problem of acquiring knowledge by integration. Our aim is to
construct an integrated knowledge base from several separate sources. The objective of …