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Supporting Social Information Discovery from Big Uncertain Social Key-Value Data via Graph-Like Metaphors

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Cognitive Computing – ICCC 2018 (ICCC 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10971))

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Abstract

In the current era of big data, huge volumes of a wide variety of valuable data of different veracity (e.g., uncertain data) can be easily collected and generated from a broad range of data sources (e.g., social networking sites) at a high velocity in various real-life applications. Many traditional data management and analytic approaches may not be suitable for handling the big data due to their well-known 5V’s characteristics. In this paper, we present a cognitive-based system for social network analysis. Our system supports information discovery of interesting social patterns from big uncertain social networks—which are represented in the form of key-value pairs—capturing the perceived likelihood of the linkages among the social entities in the network.

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Notes

  1. 1.

    https://newsroom.fb.com/company-info/.

  2. 2.

    https://about.linkedin.com/.

  3. 3.

    https://about.twitter.com/en_us/company.html.

  4. 4.

    http://snap.stanford.edu/data/.

  5. 5.

    http://aws.amazon.com/ec2/.

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Acknowledgment

This project is partially supported by Natural Sciences and Engineering Research Council of Canada (NSERC) and the University of Manitoba.

Author information

Authors and Affiliations

  1. University of Manitoba, Manitoba, MB, Canada

    Calvin S. H. Hoi, Carson K. Leung & Kimberly Tran

  2. University of Trieste, Trieste, TS, Italy

    Alfredo Cuzzocrea & Marco Simonetti

  3. ICAR-CNR, Rende, CS, Italy

    Alfredo Cuzzocrea

  4. University of Salento, Lecce, LE, Italy

    Mario Bochicchio

Authors
  1. Calvin S. H. Hoi
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  2. Carson K. Leung
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  3. Kimberly Tran
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  4. Alfredo Cuzzocrea
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  5. Mario Bochicchio
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  6. Marco Simonetti
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Corresponding author

Correspondence to Carson K. Leung .

Editor information

Editors and Affiliations

  1. Big Data Platform Division, Peking, China

    Jing Xiao

  2. University of Pittsburgh, Pittsburgh, Pennsylvania, USA

    Zhi-Hong Mao

  3. IBM Thomas J. Watson Research Center, Yorktown Heights, New York, USA

    Toyotaro Suzumura

  4. Kingdee International Software Group Co., Ltd., Shenzhen, China

    Liang-Jie Zhang

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Hoi, C.S.H., Leung, C.K., Tran, K., Cuzzocrea, A., Bochicchio, M., Simonetti, M. (2018). Supporting Social Information Discovery from Big Uncertain Social Key-Value Data via Graph-Like Metaphors. In: Xiao, J., Mao, ZH., Suzumura, T., Zhang, LJ. (eds) Cognitive Computing – ICCC 2018. ICCC 2018. Lecture Notes in Computer Science(), vol 10971. Springer, Cham. https://doi.org/10.1007/978-3-319-94307-7_8

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  • DOI: https://doi.org/10.1007/978-3-319-94307-7_8

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