Title :
Pattern Mining over Star Schemas in the Onto4AR Framework
Author :
Antunes, Cláudia
Author_Institution :
Inst. Super. Tecnico, Tech. Univ. of Lisbon, Lisbon, Portugal
Abstract :
Storing data according to the multidimensional model, in particular following star schemas, has demonstrated to be one of the most adequate forms to ease the exploration of data. However, this exploration has been limited to be query-based, leaving the discovery of hidden information to a second plan. The main reason for this, relates to the inability of traditional mining techniques to deal with several data tables at the same time. In this paper, we propose a new approach to mine patterns among data stored as a star schema, based in a domain driven framework, where available knowledge is represented in a domain ontology. Pattern mining is performed by an Apriori-based algorithm-the D2Apriori, but more efficient algorithms are being implemented and tested, in order to solve performance issues related with the large amount of data stored in data warehouses.
Keywords :
data mining; data warehouses; ontologies (artificial intelligence); D2Apriori; Onto4AR framework; data storage; data tables; data warehouses; domain ontology; pattern mining; star schemas; Association rules; Conferences; Data analysis; Data mining; Data warehouses; Multidimensional systems; Ontologies; Performance evaluation; Testing;
Conference_Titel :
Data Mining Workshops, 2009. ICDMW '09. IEEE International Conference on
Conference_Location :
Miami, FL
Print_ISBN :
978-1-4244-5384-9
Electronic_ISBN :
978-0-7695-3902-7
DOI :
10.1109/ICDMW.2009.68