Mining association rules in folksonornies

被引：66

作者：

Schmitz, Christoph ^{[1
]}

Hotho, Andreas ^{[1
]}

Jaeschke, Robert ^{[1
,2
]}

Stumme, Gerd ^{[1
,2
]}

机构：

[1] Univ Kassel, Dept Math & Comp Sci, Knowledge & Data Engn Grp, Wilhelmshher Allee 73, D-34121 Kassel, Germany

[2] Res Ctr L3S, D-30539 Hannover, Germany

来源：

DATA SCIENCE AND CLASSIFICATION | 2006年

关键词：

D O I：

10.1007/3-540-34416-0_28

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. These systems provide currently relatively few structure. We discuss in this paper, how association rule mining can be adopted to analyze and structure folksonomies, and how the results can be used for ontology learning and supporting emergent semantics. We demonstrate our approach on a large scale dataset stemming from an online system.

引用

页码：261 / +

页数：3

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