|Title||Continuous Semantics to Analyze Real-Time Data|
|Publication Type||Journal Article|
|Year of Publication||2010|
|Authors||Amit Sheth, Christopher Thomas, Pankaj Mehra|
|Journal||IEEE Internet Computing|
|Keywords||circle of knowledge life, Continuous Semantics, Doozer, Dynamic Domain model, real time search, real-time social data, semantic analysis of real-time data, semantic annotation of social data, Semantic Web|
Increasingly we are presented with dynamic domains involved in social, mobile, and sensor webs. Such domains are spontaneous (arising suddenly), follow a period of rapid evolution, involving real-time or near real-time data,involve many distributed participants and diverse viewpoints involving topical or contentious subjects, and involve feature context colored by local knowledge and sociocultural backgrounds.This article present continuous semantics can help us model such dynamic domains and analyze the related real-time data.capabilities include crating dynamic domain model by mining social data, and using dynamic models for semantic analysis of real-time data.
|Full Text|| |
Amit Sheth, Christopher Thomas, Pankaj Mehra, 'Continuous Semantics to Analyze Real-Time Data,' IEEE Internet Computing, vol. 14, no. 6, pp. 84-89, Nov./Dec. 2010, doi:10.1109/MIC.2010.137
related resource url: http://www.computer.org/portal/web/csdl/doi/10.1109/MIC.2010.137 and http://wiki.knoesis.org/index.php/Continuous_Semantics_to_Analyze_Real_T... and http://scholar.google.com/citations?view_op=view_citation&hl=en&user=2T3...