Big data deep analytics for geosocial networks

Muhammad Mazhar Ullah Rathore, Awais Ahmad, Anand Paul

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

1 Scopus citations

Abstract

Geosocial network data provides the full information on current trends in human, their behaviors, their living style, the incidents and events, the disasters, current medical infection, and much more with respect to locations. Hence, the current geosocial media can work as a data asset for facilitating the national and the government itself by analyzing the geosocial data at real-time. However, there are millions of geosocial network users, who generates terabytes of heterogeneous data with a variety of information every day with high-speed, termed as Big Data. Analyzing such big amount of data and making real-time decisions is an inspiring task. Therefore, this book chapter discusses the exploration of geosocial networks. A system architecture is discussed and implemented in a real-time environment in order to process the abundant amount of various social network data to monitor the earth events, incidents, medical diseases, user trends and thoughts to make future real-time decisions as well as future planning.

Original languageEnglish
Title of host publicationDeep Learning Innovations and Their Convergence With Big Data
PublisherIGI Global
Pages120-140
Number of pages21
ISBN (Electronic)9781522530169
ISBN (Print)1522530150, 9781522530152
DOIs
StatePublished - 13 Jul 2017

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