We describe an application of relational knowledge discovery to a key regulatory mission of the National Association of Securities Dealers (NASD). NASD is the world's largest...
The paper presents new developments in an extension of Codd’s relational model of data. The extension consists in equipping domains of attribute values with a similarity relation...
We present a method for parameter learning in relational Bayesian networks (RBNs). Our approach consists of compiling the RBN model into a computation graph for the likelihood fun...
Abstract: A study of the classes of nite relations as enriched strict monoidal categories is presented in CaS91]. The relations there are interpreted as connections in owchart sche...
This paper proposes a novel hierarchical learning strategy to deal with the data sparseness problem in relation extraction by modeling the commonality among related classes. For e...