Data Mining with Ontologies: Implementations, Findings, and Frameworks

Data Mining with Ontologies: Implementations, Findings, and Frameworks

Hector Oscar Nigro, Sandra Elizabeth Gonzalez Cisaro, Daniel Hugo Xodo
Indexed In: SCOPUS View 1 More Indices
Release Date: July, 2007|Copyright: © 2008 |Pages: 312
DOI: 10.4018/978-1-59904-618-1
ISBN13: 9781599046181|ISBN10: 1599046180|EISBN13: 9781599046204
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Description & Coverage
Description:

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.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Biomedical data mining
  • Construction of Domain Ontologies
  • Data Integration Through Protein Ontology
  • Domain Ontologies
  • Dynamic Population of Web Directories
  • Geo-Ontologies
  • Grid Data Mining Workflows
  • Integrating Ontologies and Pattern-Bases
  • Knowledge Discovery in Geographic Databases
  • Normative and Cognitive Factors in Data Mining
  • Ontology Management
  • Ontology-Based Construction
  • Ontology-Based Data Warehousing and Mining
  • Recommender Systems
  • Rule Mining in Web Marketing
  • SOM-Based Clustering of Multilingual Documents
  • TODE: An Ontology-Based Model
  • Web Usage Mining
Reviews & Statements

When we can represent and include knowledge in the process through ontologies, we can transform data mining into knowledge mining.

– Hector Oscar Nigro, Universidad Nacional del Centro de la Provin cia de Burenos Aires, Argentina

The subject of data mining and ontologies are both hot topics in information science. This collection of papers from researchers all over the world provides a diverse view of advances in data mining using ontologies. The papers are well written, with plenty of figures to support the descriptions. Useful as a resource for researchers and semantic technology developers.

– CHOICE, Vol. 45, No. 05 (2008)
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Editor/Author Biographies
Héctor Oscar Nigro received a systems engineer degree from UNICEN (Universidad Nacional del Centro de la Provincia de Buenos Aires), Tandil, Argentina; Magister degree in sociology and political sciences from FLACSO (Facultad Latinoamericana de Ciencias Sociales) and he is PhD from UBA (Universidad Nacional de Buenos Aires). He is a full professor in the Department of Computer Sciences and Systems in the Exact Sciences Faculty—UNICEN. He is the director MERAIS III—Data Mining Ontology Project (UNICEN). Also, he realizes consulting activities related to data mining, data analysis, and knowledge management for the last 15 years. His research interests are in databases, data warehouses, data mining, knowledge management, and OLAP. He has published book chapters and articles presented at various professional conferences on his research activities.
Sandra Elizabeth González Císaro was born in Mar del Plata, Argentina. She received a systems engineer degree from UNICEN (Universidad Nacional del Centro de la Provincia de Buenos Aires), Tandil, Argentina and is a PHD candidate in computational and industrial mathematics at UNICEN. She is an assistant professor at Department of Computer Sciences and Systems in the Exact Sciences Faculty, UNICEN, and she is also working on MERAIS IV Project (UNICEN). Her research interests are in databases, data warehouses, data mining, knowledge management, OLAP, symbolic data analysis and management expert systems. She has published book chapters and articles presented at various professional conferences related with her research activities. She has co-edited the book Data Mining with Ontologies: Implementations, Findings, and Frameworks, published by IGI 2008). Eng. González Císaro is an IEEE Computer Society member.
Daniel Hugo Xodo received a mathematics-physics sciences degree, industrial engineer degree and master degree in business administration from UNICEN (Universidad Nacional del Centro de la Provincia de Buenos Aires). He is a professor at Department of Computer Sciences and Systems, in the Exact Sciences Faculty, UNICEN, and a professor at UTN (Universidad Tecnológica Nacional, Regional Bahía Blanca, Argentina). He is studies group director on knowledge management (UTN), and is working on MERAIS III Project (UNICEN). His research interests are in data mining, knowledge management, management science, balanced scorecards and operations research. He has published book chapters and has articles presented at various professional conferences related with his researching. In addition, he realizes consulting activities related to his professional field.
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