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Feature Representation and Organization Method for Public Opinion Big Data Based on Association Analysis
Ist Teil von
Journal of physics. Conference series, 2021-04, Vol.1881 (3), p.32075
Ort / Verlag
Bristol: IOP Publishing
Erscheinungsjahr
2021
Quelle
EZB Electronic Journals Library
Beschreibungen/Notizen
Abstract
In order to improve the data mining level of public opinion big data, by analysing the relationship among semantic web, ontology and RDF (Resource Description Framework), the structure and organization method of public opinion big data association data are separated. Based on the analysis of network public opinion big data organization technology, and then the RDF structure definition of network public opinion knowledge map is given, and the construction method of RDF association analysis map of network public opinion knowledge is realized. Experimental research shows that the proposed method can provide more accurate correlation analysis of public opinion big data, which can effectively realize the analysis and management of public opinion hot events, and provide decision support for the management of network public opinion.