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Evaluating Decision Analytics from Mobile Big Data using Rough Set Based Ant Colony

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Mobile Big Data

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 10))

Abstract

The significance of mobile centric data from various sensors, mobile phones and from other corresponding sources has already been identified across different sections of applications from commercial services to decision making applications. However, uncertainty and volume of mobile big data solicits appropriate analytics and decision making ability to be inferred from such data sources. Primarily, the data source and analytics to be chosen from the perspective of adaptive yet intelligent technique. The proposed chapter elaborates such solution while deploying rough set, which is capable of handling imprecise and uncertain contexts of mobile big data. In addition to, ant colony pheromone deposition and evaporation process assists in optimal feature selection mechanism for resolved decisions. The proposed model is supported by case study of hazards event and the information of the event is propagated through mobile data derived from social network. The data is represented as social tweets and posts. It has been analyzed with rough set based ant colony.

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Author information

Authors and Affiliations

  1. CNRS, LIRIS, INSA de Lyon, Lyon, France

    Soumya Banerjee

  2. Birla Institute of Technology, Mesra, India

    Soumya Banerjee

  3. CNRS, LIRIS INSA, UMR5205, INSA Lyon, Universite De-Lyon, Lyon, France

    Youakim Badr

Authors
  1. Soumya Banerjee
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  2. Youakim Badr
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Correspondence to Soumya Banerjee .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Nicosia, Nicosia, Cyprus

    Georgios Skourletopoulos

  2. Department of Business Administration, Technological Educational Institute Crete, Agios Nikolaos, Greece

    George Mastorakis

  3. Department of Computer Science, University of Nicosia, Nicosia, Cyprus

    Constandinos X. Mavromoustakis

  4. Department of Computer Science and Engineering, University Politehnica of Bucharest, Bucharest, Romania

    Ciprian Dobre

  5. Department of Informatics Engineering, Technological Educational Institute of Crete, Crete, Greece

    Evangelos Pallis

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Banerjee, S., Badr, Y. (2018). Evaluating Decision Analytics from Mobile Big Data using Rough Set Based Ant Colony. In: Skourletopoulos, G., Mastorakis, G., Mavromoustakis, C., Dobre, C., Pallis, E. (eds) Mobile Big Data. Lecture Notes on Data Engineering and Communications Technologies, vol 10. Springer, Cham. https://doi.org/10.1007/978-3-319-67925-9_9

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  • DOI: https://doi.org/10.1007/978-3-319-67925-9_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67924-2

  • Online ISBN: 978-3-319-67925-9

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