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Finding Reliable Source for Event Detection Using Evolutionary Method

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Knowledge Management and Acquisition for Intelligent Systems (PKAW 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9806))

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Abstract

Participatory sensing is a phenomenon where participants use mobile phones or social media and feed data to detect an event. Since, data gathering is open to many participants, one of the major challenges of this type of networks is to identify truthfulness of the reported observations. Finding the reliable sources is a challenging task since the node or participant’s reliability is unknown or even the probability of the reported event to be true is also unknown. In our paper, we study this challenge and observe that applying evolutionary method, we can identify reliable source nodes. We call our approach Population Based Reliability Estimation. We validate our claim by experimental results. We also compare our method with another widely used method. From experiments we find that our approach is more efficient.

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Author information

Authors and Affiliations

  1. Department of CSE, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh

    Raushan Ara Dilruba & Mahmuda Naznin

  2. Department of CS, University of Calgary, Calgary, Canada

    Raushan Ara Dilruba

Authors
  1. Raushan Ara Dilruba
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  2. Mahmuda Naznin
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Corresponding author

Correspondence to Mahmuda Naznin .

Editor information

Editors and Affiliations

  1. Tokyo University of Science , Noda, Japan

    Hayato Ohwada

  2. University of Tsukuba, Tokyo, Japan

    Kenichi Yoshida

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Dilruba, R.A., Naznin, M. (2016). Finding Reliable Source for Event Detection Using Evolutionary Method. In: Ohwada, H., Yoshida, K. (eds) Knowledge Management and Acquisition for Intelligent Systems . PKAW 2016. Lecture Notes in Computer Science(), vol 9806. Springer, Cham. https://doi.org/10.1007/978-3-319-42706-5_13

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  • DOI: https://doi.org/10.1007/978-3-319-42706-5_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42705-8

  • Online ISBN: 978-3-319-42706-5

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