Social Semantic Search: A Case Study on Web 2.0 for Science

Laurens De Vocht, Selver Softic, Ruben Verborgh, Erik Mannens and Martin Ebner
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Laurens De Vocht: IDLab, Department of Electronics and Information Systems, Ghent University – imec, Ghent, Belgium
Selver Softic: Graz University of Technology, Graz, Austria
Ruben Verborgh: IDLab, Department of Electronics and Information Systems, Ghent University – imec, Ghent, Belgium
Erik Mannens: IDLab, Department of Electronics and Information Systems, Ghent University – imec, Ghent, Belgium
Martin Ebner: Graz University of Technology, Graz, Austria

International Journal on Semantic Web and Information Systems (IJSWIS), 2017, vol. 13, issue 4, 155-180

Abstract: When researchers formulate search queries to find relevant content on the Web, those queries typically consist of keywords that can only be matched in the content or its metadata. The Web of Data extends this functionality by bringing structure and giving well-defined meaning to the content and it enables humans and machines to work together using controlled vocabularies. Due the high degree of mismatches between the structure of the content and the vocabularies in different sources, searching over multiple heterogeneous repositories of structured data is considered challenging. Therefore, the authors present a semantic search engine for researchers facilitating search in research related Linked Data. To facilitate high-precision interactive search, they annotated and interlinked structured research data with ontologies from various repositories in an effective semantic model. Furthermore, the authors' system is adaptive as researchers can synchronize using new social media accounts and efficiently explore new datasets.

Date: 2017
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