DocumentCode :
1861133
Title :
Implementing Pattern Mining Using Extended Attribute Expression on Relational DB
Author :
Makino, Toshiyuki ; Inuzuka, Nobuhiro
Author_Institution :
Nagoya Inst. of Technol., Nagoya, Japan
fYear :
2010
fDate :
9-10 Jan. 2010
Firstpage :
502
Lastpage :
505
Abstract :
Multi-relational data mining (MRDM) is to enumerate frequently appeared patterns in data, the patterns which are appeared not only in a relational table but over a collection of tables. Although a database usually consists of many relational tables, most of data mining approaches treat patterns only on a table. An approach based on ILP (inductive logic programming) is a promising approach and it treats patterns on many tables. Pattern miners based on the ILP approach produce expressive patterns and are wide-applicative but computationally expensive. MAPIX has an advantage that it constructs patterns by combining atomic properties extracted from sampled examples. By restricting patterns into combinations of the atomic properties it gained efficiency compared with other algorithms. In order to scale MAPIX to treat large dataset on standard relational database systems, this paper studies implementation issues.
Keywords :
data mining; inductive logic programming; relational databases; ILP; MAPIX; MRDM; data patterns; extended attribute expression; inductive logic programming; multirelational data mining; pattern mining; relational DB; relational database systems; relational tables; Data mining; Logic programming; Relational databases; Test pattern generators; Testing; Inductive logic programming; Multi-relational data mining; Relational database;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Knowledge Discovery and Data Mining, 2010. WKDD '10. Third International Conference on
Conference_Location :
Phuket
Print_ISBN :
978-1-4244-5397-9
Electronic_ISBN :
978-1-4244-5398-6
Type :
conf
DOI :
10.1109/WKDD.2010.127
Filename :
5432516
Link To Document :
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