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Social semantic search : a case study on web 2.0 for science

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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.
Keywords
Digital Libraries, Linked Data, Research 2.0, Semantic Search, Social Media, Web 2.0, Web of Data

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Citation

Please use this url to cite or link to this publication:

MLA
De Vocht, Laurens, et al. “Social Semantic Search : A Case Study on Web 2.0 for Science.” INTERNATIONAL JOURNAL ON SEMANTIC WEB AND INFORMATION SYSTEMS, vol. 13, no. 4, 2017, pp. 155–80, doi:10.4018/IJSWIS.2017100108.
APA
De Vocht, L., Softic, S., Verborgh, R., Mannens, E., & Ebner, M. (2017). Social semantic search : a case study on web 2.0 for science. INTERNATIONAL JOURNAL ON SEMANTIC WEB AND INFORMATION SYSTEMS, 13(4), 155–180. https://doi.org/10.4018/IJSWIS.2017100108
Chicago author-date
De Vocht, Laurens, Selver Softic, Ruben Verborgh, Erik Mannens, and Martin Ebner. 2017. “Social Semantic Search : A Case Study on Web 2.0 for Science.” INTERNATIONAL JOURNAL ON SEMANTIC WEB AND INFORMATION SYSTEMS 13 (4): 155–80. https://doi.org/10.4018/IJSWIS.2017100108.
Chicago author-date (all authors)
De Vocht, Laurens, Selver Softic, Ruben Verborgh, Erik Mannens, and Martin Ebner. 2017. “Social Semantic Search : A Case Study on Web 2.0 for Science.” INTERNATIONAL JOURNAL ON SEMANTIC WEB AND INFORMATION SYSTEMS 13 (4): 155–180. doi:10.4018/IJSWIS.2017100108.
Vancouver
1.
De Vocht L, Softic S, Verborgh R, Mannens E, Ebner M. Social semantic search : a case study on web 2.0 for science. INTERNATIONAL JOURNAL ON SEMANTIC WEB AND INFORMATION SYSTEMS. 2017;13(4):155–80.
IEEE
[1]
L. De Vocht, S. Softic, R. Verborgh, E. Mannens, and M. Ebner, “Social semantic search : a case study on web 2.0 for science,” INTERNATIONAL JOURNAL ON SEMANTIC WEB AND INFORMATION SYSTEMS, vol. 13, no. 4, pp. 155–180, 2017.
@article{8545536,
  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.}},
  author       = {{De Vocht, Laurens and Softic, Selver and Verborgh, Ruben and Mannens, Erik and Ebner, Martin}},
  issn         = {{1552-6283}},
  journal      = {{INTERNATIONAL JOURNAL ON SEMANTIC WEB AND INFORMATION SYSTEMS}},
  keywords     = {{Digital Libraries,Linked Data,Research 2.0,Semantic Search,Social Media,Web 2.0,Web of Data}},
  language     = {{eng}},
  number       = {{4}},
  pages        = {{155--180}},
  title        = {{Social semantic search : a case study on web 2.0 for science}},
  url          = {{http://dx.doi.org/10.4018/IJSWIS.2017100108}},
  volume       = {{13}},
  year         = {{2017}},
}

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