Document Type
Article
Publication Date
8-2010
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.
Repository Citation
Feng, M.,
Dong, G.,
Li, J.,
Tan, Y.,
& Wong, L.
(2010). Pattern Space Maintenance for Data Updates and Interactive Mining. Computational Intelligence, 26 (3), 282-317.
https://corescholar.libraries.wright.edu/knoesis/422
DOI
10.1111/j.1467-8640.2010.00360.x
Included in
Bioinformatics Commons, Communication Technology and New Media Commons, Databases and Information Systems Commons, OS and Networks Commons, Science and Technology Studies Commons
Comments
Attached is the unpublished, peer-reviewed authors' version. The final, publisher's version of the article can be found at http://dx.doi.org/10.1111/j.1467-8640.2010.00360.x.