Semantic Filtering for Social Data

TitleSemantic Filtering for Social Data
Publication TypeMagazine Article
Year of Publication2016
AuthorsAmit Sheth, Pavan Kapanipathi
MagazineIEEE Internet Computing
Volume20
Issue Number4
Pagination74-78
Date Published08/2016
PublisherIEEE
Accession Number16191192
Keywordscollective semantics, context in social data hierarchical interest graph, Continuous Semantics, dynamically changing vocabulary, filtering social media big data, Linked Open Data, Semantic filtering, social data stream, twitris, velocity in Big Data
Abstract

More than a billion users on the Web are on social networks sharing and consuming short and real-time updates. Consumers of social data face information overload. Although information filtering can help, challenges that are specific to the short-text and real-time nature of social networks must be addressed. Knowledge bases-particularly those derived from crowd-sourced platforms such as Wikipedia can be harnessed for building an intelligent and effective information-filtering system for social networks.

DOI10.1109/MIC.2016.86
Full Text

Citation
Amit Sheth and Pavan Kapanipathi, “Semantic filtering for social data,” IEEE Internet Computing, vol. 20, pp. 74–78. 08/2016 2016. DOI: 10.1109/MIC.2016.86.

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