One of the most important and challenging problems in data mining is the definition of prior knowledge either from the process or the domain. Prior knowledge is helpful for selecting suitable data and mining techniques, pruning the space of hypothesis, representing the output in a comprehensible way, and improving the overall method. Data Mining with Ontologies: Implementations, Findings, and Frameworks provides a comprehensive set of methodologies and tools for the development of ontological foundations for data mining in diverse domains ranging from biomedicine to marketing. Forming a benchmark reference for future efforts to enhance capabilities in ontology utilization and design, this Premier Reference Source will be an invaluable addition to libraries worldwide.