Frequent Closed Pattern Mining Algorithm Based on COFI-Tree

2011 ◽  
pp. 175-182
Author(s):  
Jihai Xiao ◽  
Xiaohong Cui ◽  
Junjie Chen
Keyword(s):  
Pattern Mining ◽  
Mining Algorithm ◽  
Closed Pattern ◽  
Closed Pattern Mining

Novel techniques and an efficient algorithm for closed pattern mining

2014 ◽  
Vol 41 (11) ◽  
pp. 5105-5114 ◽  
Author(s):  
András Király ◽  
Asta Laiho ◽  
János Abonyi ◽  
Attila Gyenesei
Keyword(s):  
Efficient Algorithm ◽  
Pattern Mining ◽  
Closed Pattern ◽  
Closed Pattern Mining

scholarly journals Efficient Closed Pattern Mining in the Presence of Tough Block Constraints

2003 ◽  
Author(s):  
Krishna Gade ◽  
Jianyong Wang ◽  
George Karypis
Keyword(s):  
Pattern Mining ◽  
Closed Pattern ◽  
Closed Pattern Mining

scholarly journals Closed Pattern Mining from n-ary Relations

2010 ◽  
Vol 1 (9) ◽  
pp. 1-5 ◽  
Author(s):  
R V Nataraj ◽  
S Selvan
Keyword(s):  
Pattern Mining ◽  
Closed Pattern ◽  
Closed Pattern Mining

Distributed Mining of Closed Patterns from Multi-Relational Data

2015 ◽  
Vol 19 (6) ◽  
pp. 804-809 ◽  
Author(s):  
Yohei Kamiya ◽  
◽  
Hirohisa Seki
Keyword(s):  
Inductive Logic Programming ◽  
Formal Concept Analysis ◽  
Relational Databases ◽  
Pattern Mining ◽  
Inductive Logic ◽  
Relational Data ◽  
Formal Concept ◽  
Global Database ◽  
Closed Pattern ◽  
Closed Pattern Mining

In multi-relational data mining (MRDM), there have been proposed many methods for searching for patterns that involve multiple tables (relations) from a relational database. In this paper, we consider closed pattern mining from distributed multi-relational databases (MRDBs). Since the computation of MRDM is costly compared with the conventional itemset mining, we propose some efficient methods for computing closed patterns using the techniques studied in Inductive Logic Programming (ILP) and Formal Concept Analysis (FCA). Given a set oflocaldatabases, we first compute sets of their closed patterns (concepts) using a closed pattern mining algorithm tailored to MRDM, and then generate the set of closed patterns in the global database by utilizing themergeoperator. We also present some experimental results, which shows the effectiveness of the proposed methods.

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