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Using a Rich Context Model for Real-Time Big Data Analytics in Twitter
Linnaeus University, Faculty of Technology, Department of Media Technology. (CeLeKT)ORCID iD: 0000-0001-9062-1609
Linnaeus University, Faculty of Technology, Department of Media Technology.ORCID iD: 0000-0001-7072-1063
Linnaeus University, Faculty of Technology, Department of Media Technology. (CeLeKT)ORCID iD: 0000-0002-6937-345X
Linnaeus University, Faculty of Technology, Department of Media Technology. Telenor Grp, Norway. (CeLeKT)
2016 (English)In: 2016 IEEE 4TH INTERNATIONAL CONFERENCE ON FUTURE INTERNET OF THINGS AND CLOUD WORKSHOPS (FICLOUDW), IEEE, 2016, p. 228-233Conference paper, Published paper (Refereed)
Abstract [en]

In this paper we present an approach for contextual big data analytics in social networks, particularly in Twitter. The combination of a Rich Context Model (RCM) with machine learning is used in order to improve the quality of the data mining techniques. We propose the algorithm and architecture of our approach for real-time contextual analysis of tweets. The proposed approach can be used to enrich and empower the predictive analytics or to provide relevant context-aware recommendations.

Place, publisher, year, edition, pages
IEEE, 2016. p. 228-233
Keywords [en]
rich context model, big data, context analytics, twitter, k-means clustering
National Category
Media and Communication Technology
Research subject
Computer and Information Sciences Computer Science, Media Technology
Identifiers
URN: urn:nbn:se:lnu:diva-58342DOI: 10.1109/W-FiCloud.2016.55ISI: 000386667700037Scopus ID: 2-s2.0-85009830198ISBN: 978-1-5090-3946-3 (print)ISBN: 978-1-5090-3947-0 (print)OAI: oai:DiVA.org:lnu-58342DiVA, id: diva2:1050865
Conference
IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW), AUG 22-24, 2016, Vienna, AUSTRIA
Available from: 2016-11-30 Created: 2016-11-28 Last updated: 2018-01-13Bibliographically approved

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Sotsenko, AlisaJansen, MarcMilrad, MarceloRana, Juwel

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf