BEST: An Efficient Algorithm for Mining Frequent Unordered Embedded Subtrees

被引：0

作者：

Chowdhury, Israt Jahan ^{[1
]}

Nayak, Richi ^{[1
]}

机构：

[1] Queensland Univ Technol, Sch Elect Engn & Comp Sci, Fac Sci & Engn, Brisbane, Qld 4001, Australia

来源：

PRICAI 2014: TRENDS IN ARTIFICIAL INTELLIGENCE | 2014年 / 8862卷

关键词：

Frequent subtrees; labelled rooted unordered trees; embedded subtrees; canonical form; enumeration approach; TREES;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents an algorithm for mining unordered embedded subtrees using the balanced-optimal-search canonical form (BOCF). A tree structure guided scheme based enumeration approach is defined using BOCF for systematically enumerating the valid subtrees only. Based on this canonical form and enumeration technique, the balanced optimal search embedded subtree mining algorithm (BEST) is introduced for mining embedded subtrees from a database of labelled rooted unordered trees. The extensive experiments on both synthetic and real datasets demonstrate the efficiency of BEST over the two state-of-the-art algorithms for mining embedded unordered subtrees, SLEUTH and U3.

引用

页码：459 / 471

页数：13

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