In this paper, we pose a novel research problem for machine learning that involves constructing a process model from continuous data. We claim that casting learned knowledge in ter...
Will Bridewell, Pat Langley, Ljupco Todorovski, Sa...
Scientists use two forms of knowledge in the construction of explanatory models: generalized entities and processes that relate them; and constraints that specify acceptable combi...
—This paper presents power flow models of a self-excited induction generator. These models are used for steady-state power flow calculation in electric power systems in which a g...
This paper presents a novel approach to the unsupervised learning of syntactic analyses of natural language text. Most previous work has focused on maximizing likelihood according...
Distributional similarity methods have proven to be a valuable tool for the induction of semantic similarity. Up till now, most algorithms use two-way cooccurrence data to compute...