Paper Info
Title
Facilitating Active Multidimensional Association Mining with User Preference Ontology
Abstract
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.
Year
DOI
Venue
2009
10.1109/WI-IAT.2009.320
Web Intelligence/IAT Workshops
Keywords
Field
DocType
users dynamically,renewal mining result,specific user,active multidimensional association mining,target mining data,reinitiate mining query,data warehouse,user preference ontology,multidimensional association mining,active mining mechanism,intelligent agent,ontology,association rule mining,knowledge management,data warehouses,multidimensional systems,association rules,business rules,data mining,knowledge discovery,ontologies,information management
Data warehouse,Ontology (information science),Data science,Data mining,Data stream mining,Concept mining,User profile,Information retrieval,Computer science,Association rule learning,Knowledge extraction,Business rule
Conference
Citations 
PageRank 
References 
0
0.34
6
Authors
3
Name
Order
Citations
PageRank
Chin-Ang Wu1152.37
Wen-Yang Lin239935.72
Chuan-Chun Wu3133.99