Modeling and Mining Optimal Patterns using Dynamic CSP

被引：2
作者：
Ugarte, Willy [1 ]
Boizumault, Patrice [1 ]
Cremilleux, Bruno [1 ]
Loudni, Samir [1 ]
机构：
[1] Univ Caen Basse Normandie, CNRS UMR 6072, GREYC Lab, F-14032 Caen, France
来源：
2015 IEEE 27TH INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI 2015) | 2015年
关键词：
Pattern Mining; Optimisation; Dynamic CSP; DISCOVERY; KNOWLEDGE; SET;
D O I：
10.1109/ICTAI.2015.19
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We introduce the notion of Optimal Patterns (OPs), defined as the best patterns according to a given user preference, and show that OPs encompass many data mining problems. Then, we propose a generic method based on a Dynamic Constraint Satisfaction Problem to mine OPs, and we show that any OP is characterized by a basic constraint and a set of constraints to be dynamically added. Finally, we perform an experimental study comparing our approach vs ad hoc methods on several types of OPs.
引用
收藏
页码：33 / 40
页数：8
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