4.7 Article

Fuzzy queries of social networks with FSA-SPARQL

期刊

EXPERT SYSTEMS WITH APPLICATIONS
卷 113, 期 -, 页码 128-146

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2018.06.051

关键词

SPARQL; Semantic web; Fuzzy logic; Database query languages; Social networks

资金

  1. FEDER
  2. State Research Agency (AEI) of the Spanish Ministry of Economy and Competition [TIN2013-44742-C4-4-R, TIN2016-76843-C4-2-R]

向作者/读者索取更多资源

Social networks have become a source of data which are of interest in all areas, and their querying and analysis is a hot topic in computer science. Our research group has developed a fuzzy extension of the Semantic Web query language SPARQL, called FSA-SPARQL (Fuzzy Sets and Aggregators based SPARQL). This extension provides mechanisms to express fuzzy queries against RDF data. FSA-SPARQL works with social networks. With this aim, FSA-SPARQL enables the transformation and fuzzification of social network API data. Fuzzification of social networks data is automatic and user-defined enabling a wide range of mechanisms for ranking and categorization, including sentiment analysis and topic detection. As a case study, FSA-SPARQL has been used to query three well-known social networks: Twitter, Foursquare and TMDb. (C) 2018 Elsevier Ltd. All rights reserved.

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