Facilitating Active Multidimensional Association Mining with User Preference Ontology

• Published in: Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 03 Vol. 3; pp. 437 - 440
• Main Authors: Wu, Chin-Ang, Lin, Wen-Yang, Wu, Chuan-Chun
• Format: Conference Proceeding
• Language: English
• Published: Washington, DC, USA IEEE Computer Society 15.09.2009; IEEE
• Series: ACM Conferences
• Subjects: Active mining; Association rules; Computing methodologies > Artificial intelligence > Knowledge representation and reasoning; Computing methodologies > Artificial intelligence > Knowledge representation and reasoning > Semantic networks; Computing methodologies > Machine learning > Machine learning approaches > Rule learning; Conferences; Data mining; Data warehouse mining; Data warehouses; Electronic mail; Information management; Information systems > Data management systems > Information integration > Data warehouses; Information systems > Information retrieval > Users and interactive retrieval > Personalization; Information systems > Information systems applications > Data mining; Information systems > Information systems applications > Decision support systems > Data warehouses; Information systems > World Wide Web > Web searching and information discovery > Personalization; Intelligent agent; Knowledge management; Multidimensional association rule mining; Multidimensional systems; Ontologies; Ontology; Multidimensional association rule mining; Ontology; Active mining; Data warehouse mining
• ISBN: 0769538010; 9780769538013
• DOI: 10.1109/WI-IAT.2009.320

Multidimensional association mining from data warehouse has become a knowledge discovery paradigm because it provides more specific conditional settings for target mining data, thus can generate rules more close to users’ needs. Yet data warehouse is subject to change by time or the modifications of business rules. Users might not know this change and reinitiate mining queries, which elicits the necessity of an active mining mechanism to bring new knowledge to users dynamically. In this paper, we propose an active multidimensional association mining system framework that incorporates with the user preference ontology that exploits frequent and representative queries. With the assistance of the user preference ontology and its association with user profile, the proposed system can facilitate active mining mechanism, allowing distribution of the renewal mining results to the specific users automatically.