Instance matching based on discriminative property values

Ghemmaz, Wafa; Benchikha, Fouzia

doi:10.1109/icta.2015.7426892

Cited by 3 publications

(5 citation statements)

References 7 publications

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“…For example, a property can be classified as a Discriminative or a Descriptive property. The former (eg, rdf:type) can be used directly to distinguish the instances, while the latter (eg, rdfs:comment) can rather be used to describe the instances …”

Section: Discussionmentioning

confidence: 99%

“…In Reference , the authors use the discriminative properties to generate candidates. A light version of identity link called ViewSameAs is defined to track the instances sharing discriminative property values.…”

Section: Discussionmentioning

confidence: 99%

“…The ViewSameAs is replaced by an identity link between the master instance and each instance in that bag. References and did not provide any evaluation showing the effectiveness of their approaches.…”

Section: Discussionmentioning

confidence: 99%

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Data linking over RDF knowledge graphs: A survey

Assi

Mcheick

Dhifli³

2020

Concurrency and Computation

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Summary Instance matching (IM) is the process of matching instances across Knowledge Bases (KBs) that refer to the same real‐world object (eg, the same person in two different KBs). Several approaches in the literature were developed to perform this process using different algorithmic techniques and search strategies. In this article, we aim to provide the rationale for IM and to survey the existing algorithms for performing this task. We begin by identifying the importance of such a process and define it formally. We also provide a new classification of these approaches depending on the “source of evidence,” which can be considered as the context information integrated explicitly or implicitly in the IM process. We survey and discuss the state‐of‐the‐art IM methods regarding the context information. We, furthermore, describe and compare different state‐of‐the‐art IM approaches in relation to several criteria. Such a comprehensive comparative study constitutes an asset and a guide for future research in IM.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Data linking over RDF knowledge graphs: A survey

Assi

Mcheick

Dhifli³

2020

Concurrency and Computation

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“…• IM-PC: is performed in two main steps (Ghemmaz and Benchikha, 2015): the candidate selection and the result refinement. The former is based on the discriminative property values and the later is based on descriptive property values.…”

Section: Approach Overviewmentioning

confidence: 99%

“…It keeps the track of instances which share important properties especially discriminative ones. These instances could be identical and refer to the same real word object or they could be different but considering as similar according to an agent viewpoint (Ghemmaz and Benchikha, 2015).…”

Section: The Viewsameas Linkmentioning

confidence: 99%

ViewSameAs: A Novel Link in Instance Matching Process

Ghemmaz

Benchikha

2016

Proceedings of the 12th International Conference on Web Information Systems and Technologies

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In recent years, the Web has evolved from a global information space of interlinked documents to a space where both documents and data are linked. To integrate and share data, instance matching has been become the fundamental issue especially with the rapid development of linked data. In this paper, we propose an instance matching approach based on two main processes: the former is based on property classification (IM_PC) and the later is based on ViewSameAs link (IM_VSA). To accelerate greatly the matching process, IM_PC determines at first the matching candidate by comparing the discriminative property values. Then, the refinement result is done by comparing the description property values. In IM_PC two links are established: identity SameAs link and a novel proposed link ViewSameAs that aims to keep track of instances which share similar discriminative property values. In instance matching, another problem should be addressed when instances may have different descriptions even if their meanings are similar. So, this problem is addressed in IM_VSA process. The aim of this later is trying to get more identity link SameAs by Clustering instances matched with ViewSameAs. The Clustered instances are modeled as bags.

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A Personalized Ontology Model For Web Mining Using Instance Matching

Pawar¹

2016

IJECS

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Instance matching based on discriminative property values

Cited by 3 publications

References 7 publications

Data linking over RDF knowledge graphs: A survey

Data linking over RDF knowledge graphs: A survey

ViewSameAs: A Novel Link in Instance Matching Process

A Personalized Ontology Model For Web Mining Using Instance Matching

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