Using Market Basket Analysis to Find Semantic Duplicates in Ontology

被引：2

作者：

Astrova, Irina ^{[1
]}

Koschel, Arne ^{[2
]}

Lee, Su Ling ^{[2
]}

机构：

[1] Tallinn Univ Technol, Dept Software Sci, Sch IT, Akad Tee 21, EE-12618 Tallinn, Estonia

[2] Univ Appl Sci & Arts Hannover, Fac 4, Dept Comp Sci, Ricklinger Stadtweg 120, D-30459 Hannover, Germany

来源：

COMPUTATIONAL SCIENCE AND ITS APPLICATIONS, ICCSA 2020, PART IV | 2020年 / 12252卷

关键词：

Ontolgy; Semantic heterogeneity; Market basket analysis; Apriori algorithm; FP Growth (Frequent-Pattern Growth) algorithm; ICD (Iterated Contextual Distance) algorithm; Similar attributes; OntoLife ontology;

D O I：

10.1007/978-3-030-58811-3_14

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

This paper proposes a novel approach to detecting semantic duplicates in an ontology that was integrated from many other ontologies. The proposed approach is based on using: (1) a query log that was issued against the ontology; and (2) the Apriori and FP algorithms from market basket analysis, where sales transactions are viewed as queries and items in a sales transaction are viewed as search terms in a query. To prove the viability of the proposed approach, the paper also presents the results of four experiments that were conducted on the OntoLife ontology.

引用

页码：197 / 211

页数：15

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