|Title||Semantic Filtering for Social Data|
|Publication Type||Magazine Article|
|Year of Publication||2016|
|Authors||Amit Sheth, Pavan Kapanipathi|
|Magazine||IEEE Internet Computing|
|Keywords||collective 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|
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.
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