Data mining has been widely recognized as a powerful tool to explore added value from large-scale databases. One of data mining techniques, generalized association rule mining wit...
This paper introduces a new approach to a problem of data sharing among multiple parties, without disclosing the data between the parties. Our focus is data sharing among two parti...
Association rule mining is an important data analysis tool that can be applied with success to a variety of domains. However, most association rule mining algorithms seek to discov...
In this paper we examine the effect that the choice of support and confidence thresholds has on the accuracy of classifiers obtained by Classification Association Rule Mining. ...
Association rule mining in real-time is of increasing thrust in many business applications. Applications such as e-commerce, recommender systems, supply-chain management and group...
Association rule mining has made many achievements in the area of knowledge discovery in databases. Recent years, the quality of the extracted association rules has drawn more and...
Outsourcing association rule mining to an outside service provider brings several important benefits to the data owner. These include (i) relief from the high mining cost, (ii) m...
Wai Kit Wong, David W. Cheung, Edward Hung, Ben Ka...
Recommender systems apply knowledge discovery techniques to help in finding associated information. In this paper, we investigate the use of association rule mining as an underlyi...
A Classification Association Rule (CAR), a common type of mined knowledge in Data Mining, describes an implicative co-occurring relationship between a set of binary-valued data-att...
To date, most association rule mining algorithms have assumed that the domains of items are either discrete or, in a limited number of cases, hierarchical, categorical or linear. ...