Semantic Matching Through Knowledge Graphs: A Smart City Case

Semantic Matching Through Knowledge Graphs: A Smart City Case

Abstract

Using selected building blocks of the Semantic Web vision to enhance domain-specific modeling methods is advancing as a new research area. The study at hand aims to contribute to this novel area of research by proposing a Semantic Matching Model that serves as a foundation for matching the purpose of a certain modeling method with the intention of future users. Within this matching model, Linked Open Data is utilized to semantically align user inputs in the form of words or phrases with resources from the Semantic Web, which can then form the basis for semantic enrichment of model instances. An experimental proof-of-concept is provided in the form of a smart city-related implementation scenario. In this scenario, tour models are first matched with relevant information from the Semantic Web and then translated into semantic-rich knowledge graphs that enable the publication of the enriched models.

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Authors
  • Voelz, Alexander
  • Amlashi, Danial M.
  • Lee, Moonkun
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Shortfacts
Category
Paper in Conference Proceedings or in Workshop Proceedings (Paper)
Event Title
35th International Conference on Advanced Information Systems Engineering (CAiSE'23)
Divisions
Knowledge Engineering
Subjects
Informatik Sonstiges
Event Location
Zaragoza, Spain
Event Type
Workshop
Event Dates
12.06 - 16.06.2023
Series Name
Advanced Information Systems Engineering Workshops
Publisher
Springer International Publishing
Page Range
pp. 92-104
Date
2023
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