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A Survey on Big Data and Collective Intelligence

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Algorithmic Aspects of Cloud Computing (ALGOCLOUD 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10230))

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Abstract

The creation and accumulation of Big Data is a fact for a plethora of scenarios nowadays. Sources such as the ever-increasing diversity sensors as well as the content created by humans have contributed to the Big Data’s enormous size and unique characteristics. Making sense of these data has primarily rested upon Big Data analysis algorithms. Still, in one too many cases the effectiveness of these algorithms is hampered by the very nature of Big Data: analogue, noisy, implicit, and ambiguous. Enter Collective Intelligence: the capability of interconnected intelligences achieving ameliorated results in activities than each of the single intelligences creating the collective solely would. Accordingly, this work presents existing research on Big Data and Collective Intelligence. The work is concluded with the presentation of the challenges and perspectives of the common ground between the directions of Big Data and Collective Intelligence.

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Notes

  1. 1.

    https://en.wikipedia.org/wiki/Collective_intelligence.

  2. 2.

    http://www.linuxfoundation.org/.

  3. 3.

    Henceforth appearing with a capital first V in order to denote the specific meaning these have for Big Data.

  4. 4.

    An extensive presentation of the service and deployment models is outside the scope of this work. Interested readers are referred to [21].

  5. 5.

    http://hadoop.apache.org/.

  6. 6.

    Collective behaviour in animals displaying intelligence attributes is established but outside the scope of this work. Interested readers are referred to Chap. 4 of [18].

  7. 7.

    Interested readers are referred to Chap. 5 of [18] for an extensive set of Collective Intelligence forecasting examples.

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Authors and Affiliations

  1. Ionian University, 49132, Kerkyra, Greece

    Ioannis Karydis, Spyros Sioutas, Markos Avlonitis & Phivos Mylonas

  2. University of Patras, 26504, Patra, Greece

    Andreas Kanavos

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  1. Ioannis Karydis
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  2. Spyros Sioutas
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  3. Markos Avlonitis
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  4. Phivos Mylonas
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  5. Andreas Kanavos
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Correspondence to Ioannis Karydis .

Editor information

Editors and Affiliations

  1. Computer Science and Software Engineering, Swinburne University of Technology, Hawthorn, Victoria, Australia

    Timos Sellis

  2. Informatics, Ionian University, Kerkyra, Greece

    Konstantinos Oikonomou

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Karydis, I., Sioutas, S., Avlonitis, M., Mylonas, P., Kanavos, A. (2017). A Survey on Big Data and Collective Intelligence. In: Sellis, T., Oikonomou, K. (eds) Algorithmic Aspects of Cloud Computing. ALGOCLOUD 2016. Lecture Notes in Computer Science(), vol 10230. Springer, Cham. https://doi.org/10.1007/978-3-319-57045-7_11

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  • DOI: https://doi.org/10.1007/978-3-319-57045-7_11

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