Social Semantic Search: A Case Study on Web 2.0 for Science
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, we present a semantic search engine for researchers facilitating search in research related Linked Data. To facilitate high-precision interactive search, we configured the engine to annotate and interlink structured research data with ontologies from various repositories in an effective semantic model. Furthermore, our system is adaptive as researchers can choose to add their social media accounts for synchronization and efficiently explore new datasets.
Published in 2017 in International Journal On Semantic Web and Information Systems.
- Web
- Linked Data
- social media
- metadata
- research
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Cite this article easily using its BibTeX entry:
@article{devocht_ijswis_2017,
title = {Social Semantic Search: A Case Study on {Web~2.0} for Science},
author = {De Vocht, Laurens and Softic, Selver and Verborgh, Ruben and Mannens, Erik and Ebner, Martin and Van de Walle, Rik},
journal = {International Journal On Semantic Web and Information Systems},
year = 2017,
month = oct,
volume = 13,
number = 4,
pages = {155--180},
doi = {10.4018/IJSWIS.2017100108},
}
Alternatively, pick a reference of your choice below:
- ACM
- Laurens De Vocht, Selver Softic, Ruben Verborgh, Erik Mannens, Martin Ebner, and Rik Van de Walle. 2017. Social Semantic Search: A Case Study on Web 2.0 for Science. International Journal On Semantic Web and Information Systems 13, 4 (October 2017), 155–180.
- APA
- De Vocht, L., Softic, S., Verborgh, R., Mannens, E., Ebner, M., & Van de Walle, R. (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.
- IEEE
- L. De Vocht, S. Softic, R. Verborgh, E. Mannens, M. Ebner, and R. Van de Walle, “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, Oct. 2017.
- LNCS
- De Vocht, L., Softic, S., Verborgh, R., Mannens, E., Ebner, M., Van de Walle, R.: Social Semantic Search: A Case Study on Web 2.0 for Science. International Journal On Semantic Web and Information Systems. 13, 155–180 (2017).
- 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, Oct. 2017, pp. 155–80.
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