Distributed Uncertain Data Mining for Frequent Patterns Satisfying Anti-monotonic Constraints

Author

Leung, Carson Kai-Sang ; MacKinnon, Richard Kyle ; Fan Jiang

Author_Institution

Dept. of Comput. Sci., Univ. of Manitoba, Winnipeg, MB, Canada

fYear

2014

fDate

13-16 May 2014

Firstpage

1

Lastpage

6

Abstract

High volumes of uncertain data can be generated in distributed environments in many real-life biological, medical and life science applications. As an important data mining task, frequent pattern mining helps discover frequently co-occurring items, objects, or events from these distributed databases. However, users may be interested in only some small portions of all the frequent patterns that can be mined from these databases. In this paper, we propose an intelligent computing system that (i) allows users to express their interests via the use of user-specified constraints and (ii)effectively exploits anti-monotonic properties of user-specified constraints and efficiently discovers frequent patterns satisfying these constraints from the distributed databases containing uncertain data.

Keywords

data mining; distributed databases; anti-monotonic constraints; distributed databases; distributed environments; distributed uncertain data mining; frequent pattern mining; intelligent computing system; uncertain data; user-specified constraints; Computer aided manufacturing; Computer science; Data mining; Distributed databases; Runtime; Sensors; anti-monotonic constraints; constraints; data mining; distributed data mining; frequent patterns; intelligent computing; uncertain data;

fLanguage

English

Publisher

ieee

Conference_Titel

Advanced Information Networking and Applications Workshops (WAINA), 2014 28th International Conference on

Conference_Location

Victoria, BC

Print_ISBN

978-1-4799-2652-7

Type

conf

DOI

10.1109/WAINA.2014.11

Filename

6844604