Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6854700 | Expert Systems with Applications | 2018 | 49 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Jesús M. Almendros-Jiménez, Antonio Becerra-Terón, Ginés Moreno,