EXiT-B: A new approach for extracting maximal frequent subtrees from XML data

被引：0

作者：

Paik, J ^{[1
]}

Won, D ^{[1
]}

Fotouhi, F ^{[1
]}

Kim, UM ^{[1
]}

机构：

[1] Sungkyunkwan Univ, Dept Comp Engn, Suwon 440746, Gyeonggi Do, South Korea

来源：

INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING IDEAL 2005, PROCEEDINGS | 2005年 / 3578卷

关键词：

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：

Along with the increasing amounts of XML data available, the data mining community has been motivated to discover the useful information from the collections of XML documents. One of the most popular approaches to find the information is to extract frequent subtrees from a set of XML trees. In this paper, we propose a novel algorithm, EXiT-B, for efficiently extracting maximal frequent subtrees from a set of XML documents. The main contribution of our algorithm is that there is no need to perform tree join operation during the phase of generating maximal frequent subtrees. Thus, the task of finding maximal frequent subtrees can be significantly simplified comparing to the previous approaches.

引用

页码：1 / 8

页数：8

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