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Towards OLAP Analysis of Multidimensional Tweet Streams

Published:22 October 2015Publication History

ABSTRACT

Social media and networks are used by millions of people to share with their friends across the world: tastes, opinions, ideas, etc. The volume and the speed at which these data are produced make it a challenging task to discover meaningful patterns in the data. Nevertheless, very interesting business goals could be achieved collecting these data and performing analytics on social media data streams, such as: addressing marketing strategies, targeting advertisements, and so forth. We emphasize that there is a need to investigate and define suitable knowledge mining approaches to go beyond explicitly available metadata by analyzing unstructured data to provide intelligent analytics services. Specifically, in this paper we provide first results on applying OLAP analysis to multidimensional Tweet streams.

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      • Published in

        cover image ACM Conferences
        DOLAP '15: Proceedings of the ACM Eighteenth International Workshop on Data Warehousing and OLAP
        October 2015
        108 pages
        ISBN:9781450337854
        DOI:10.1145/2811222

        Copyright © 2015 ACM

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        Publication History

        • Published: 22 October 2015

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        DOLAP '15 Paper Acceptance Rate8of31submissions,26%Overall Acceptance Rate29of79submissions,37%

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