Please use this identifier to cite or link to this item: https://doi.org/10.1111/j.1467-8640.2010.00360.x
Title: Pattern space maintenance for data updates and interactive mining
Authors: Feng, M. 
Dong, G.
Li, J.
Tan, Y.-P.
Wong, L. 
Keywords: data mining
data update and interactive mining
frequent pattern
incremental maintenance
Issue Date: 2010
Source: Feng, M.,Dong, G.,Li, J.,Tan, Y.-P.,Wong, L. (2010). Pattern space maintenance for data updates and interactive mining. Computational Intelligence 26 (3) : 282-317. ScholarBank@NUS Repository. https://doi.org/10.1111/j.1467-8640.2010.00360.x
Abstract: This article addresses the incremental and decremental maintenance of the frequent pattern space. We conduct an in-depth investigation on how the frequent pattern space evolves under both incremental and decremental updates. Based on the evolution analysis, a new data structure, Generator-Enumeration Tree (GE-tree), is developed to facilitate the maintenance of the frequent pattern space. With the concept of GE-tree, we propose two novel algorithms, Pattern Space Maintainer+ (PSM+) and Pattern Space Maintainer- (PSM-), for the incremental and decremental maintenance of frequent patterns. Experimental results demonstrate that the proposed algorithms, on average, outperform the representative state-of-the-art methods by an order of magnitude. © 2010 Wiley Periodicals, Inc.
Source Title: Computational Intelligence
URI: http://scholarbank.nus.edu.sg/handle/10635/39071
ISSN: 08247935
DOI: 10.1111/j.1467-8640.2010.00360.x
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