Generalization Data Mining in Fuzzy Object-Oriented Databases

Generalization Data Mining in Fuzzy Object-Oriented Databases

Rafal Angryk, Roy Ladner, Frederick E. Petry
ISBN13: 9781599049519|ISBN10: 1599049511|EISBN13: 9781599049526
DOI: 10.4018/978-1-59904-951-9.ch126
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MLA

Angryk, Rafal, et al. "Generalization Data Mining in Fuzzy Object-Oriented Databases." Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications, edited by John Wang, IGI Global, 2008, pp. 2121-2140. https://doi.org/10.4018/978-1-59904-951-9.ch126

APA

Angryk, R., Ladner, R., & Petry, F. E. (2008). Generalization Data Mining in Fuzzy Object-Oriented Databases. In J. Wang (Ed.), Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications (pp. 2121-2140). IGI Global. https://doi.org/10.4018/978-1-59904-951-9.ch126

Chicago

Angryk, Rafal, Roy Ladner, and Frederick E. Petry. "Generalization Data Mining in Fuzzy Object-Oriented Databases." In Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications, edited by John Wang, 2121-2140. Hershey, PA: IGI Global, 2008. https://doi.org/10.4018/978-1-59904-951-9.ch126

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Abstract

In this chapter, we consider the application of generalization-based data mining to fuzzy similarity-based object-oriented databases (OODBs). Attribute generalization algorithms have been most commonly applied to relational databases, and we extend these approaches. A key aspect of generalization data mining is the use of a concept hierarchy. The objects of the database are generalized by replacing specific attribute values by the next higher-level term in the hierarchy. This will then eventually result in generalizations that represent a summarization of the information in the database. We focus on the generalization of similarity-based simple fuzzy attributes for an OODB using approaches to the fuzzy concept hierarchy developed from the given similarity relation of the database. Then consideration is given to applying this approach to complex structure-valued data in the fuzzy OODB.

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