XML schema clustering with semantic and hierarchical similarity measures

被引：32

作者：

Nayak, Richi ^{[1
]}

Iryadi, Wina ^{[1
]}

机构：

[1] Queensland Univ Technol, Sch Informat Sci, Brisbane, Qld 4001, Australia

来源：

KNOWLEDGE-BASED SYSTEMS | 2007年 / 20卷 / 04期

关键词：

clustering; data mining; document mining; XML; semi-structured data; semantic similarity; structural similarity; schema matching;

D O I：

10.1016/j.knosys.2006.08.006

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

With the growing popularity of XML as the data representation language, collections of the XML data are exploded in numbers. The methods are required to manage and discover the useful information from them for the improved document handling. We present a schema clustering process by organising the heterogeneous XML schemas into various groups. The methodology considers not only the linguistic and the context of the elements but also the hierarchical structural similarity. We support our findings with experiments and analysis. (c) 2006 Elsevier B.V. All rights reserved.

引用

页码：336 / 349

页数：14

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