Flexible online association rule mining based on multidimensional pattern relations

Most incremental mining and online mining algorithms concentrate on finding association rules or patterns consistent with entire current sets of data. Users cannot easily obtain results from only interesting portion of data. This may prevent the usage of mining from online decision support for multidimensional data. To provide ad-hoc, query-driven, and online mining support, we first propose a relation called the multidimensional pattern relation to structurally and systematically store context and mining information for later analysis. Each tuple in the relation comes from an inserted dataset in the database. We then develop an online mining approach called three-phase online association rule mining (TOARM) based on this proposed multidimensional pattern relation to support online generation of association rules under multidimensional considerations. The TOARM approach consists of three phases during which final sets of 0020-0255/$ see front matter 2005 Elsevier Inc. All rights reserved. doi:10.1016/j.ins.2005.05.005 * Corresponding author. Tel.: +886 3 571 2121x56658; fax: +886 3 572 1490. E-mail addresses: [email protected], [email protected] (C.-Y. Wang), sstseng@ cis.nctu.edu.tw (S.-S. Tseng), [email protected] (T.-P. Hong). C.-Y. Wang et al. / Information Sciences 176 (2006) 1752–178