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Modeling, Generating, and Publishing Knowledge as Linked Data Read chapter Read first chapter

2017 | OriginalPaper | Chapter

The SemaDrift Protégé Plugin to Measure Semantic Drift in Ontologies: Lessons Learned

Authors : Thanos G. Stavropoulos, Stelios Andreadis, Efstratios Kontopoulos, Marina Riga, Panagiotis Mitzias, Ioannis Kompatsiaris

Published in: Knowledge Engineering and Knowledge Management

Publisher: Springer International Publishing

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Abstract

Semantic drift is an active research field, which aims to identify and measure changes in ontologies across time and versions. Yet, only few practical methods have emerged that are directly applicable to Semantic Web constructs, while the lack of relevant applications and tools is even greater. This paper presents the findings, current limitations and lessons learned throughout the development and the application of a novel software tool, developed in the context of the PERICLES FP7 project, which integrates currently investigated methods, such as text and structural similarity, into the popular ontology authoring platform, Protégé. The graphical user interface provides knowledge engineers and domain experts with access to methods and results without prior programming knowledge. Its applicability and usefulness are validated through two proof-of-concept scenarios in the domains of Web Services and Digital Preservation; especially the latter is a field where such long-term insights are crucial.

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previous chapter Tracing Shifting Conceptual Vocabularies Through Time
next chapter Combining Distributional Semantics and Structured Data to Study Lexical Change
Footnotes
1
The Protégé Ontology Editor: http://​protege.​stanford.​edu.
 
2
PERICLES FP7 project: www.​pericles-project.​eu.
 
8
Partnership with TATE within the context of the PERICLES FP7 project provided realistic knowledge for the generated models.
 
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Metadata
Title
The SemaDrift Protégé Plugin to Measure Semantic Drift in Ontologies: Lessons Learned
Authors
Thanos G. Stavropoulos
Stelios Andreadis
Efstratios Kontopoulos
Marina Riga
Panagiotis Mitzias
Ioannis Kompatsiaris
Copyright Year
2017
Book
Knowledge Engineering and Knowledge Management

Print ISBN: 978-3-319-58693-9

Electronic ISBN: 978-3-319-58694-6

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-58694-6_3

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