This dissertation studies the problem of clustering objects represented by relational data. This is a pertinent problem as many real-world data sets can only be

Ontologies are now increasingly used to integrate, and organize data and knowledge, particularly in data and knowledge-intensive applications in both research a

Presently, a growing number of ontologies are being built and used for annotating data in biomedical research. Thanks to the tremendous amount of data being gen

A culmination of the authors' years of extensive research on this topic, Relational Data Clustering: Models, Algorithms, and Applications addresses the fundamen