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A Hybrid Approach for Recommender Systems in a Proximity Based Social Network

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Smart and Sustainable Engineering for Next Generation Applications (ELECOM 2018)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 561))

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Abstract

Being one of the latest trends in technology, big data is proving to be fundamental in various fields and domains. Analyzing the large volume of data leads to fruitful information and depicts new methods of achieving growth and innovation in this competitive world. Similarly, analyzing large data sets from social media can enhance recommendations provided by recommender systems in a proximity based social network. This research work presents a hybrid approach for performing recommendations in a proximity based social network by using three recommendation techniques namely Content-based filtering, Collaborative filtering and Link Analysis. Additionally, big data from social media is analyzed to enhance the recommendations. The Hadoop ecosystem is used to help for processing large datasets. A prototype has been implemented and evaluated.

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Author information

Authors and Affiliations

  1. Department of Software and Information Systems, Faculty of Information, Communication and Digital Technologies, University of Mauritius, Réduit, Mauritius

    Soulakshmee D. Nagowah

  2. Department of Information and Communication Technologies, Faculty of Information, Communication and Digital Technologies, University of Mauritius, Réduit, Mauritius

    Kedarnathsingh Rajarai & Muhammad M. N. Lallmahamood

Authors
  1. Soulakshmee D. Nagowah
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  2. Kedarnathsingh Rajarai
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  3. Muhammad M. N. Lallmahamood
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Corresponding author

Correspondence to Soulakshmee D. Nagowah .

Editor information

Editors and Affiliations

  1. Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, UK

    Peter Fleming

  2. Transnet Centre of Systems Engineering, University of the Witwatersrand, Wits, South Africa

    Beatrys Margaretha Lacquet

  3. Department of Computer Science, University of Surrey, Guildford, UK

    Saeid Sanei

  4. Michigan State University , East Lansing, MI, USA

    Kalyanmoy Deb

  5. Department of Mathematical Statistics, Lund University, Lund, Sweden

    Andreas Jakobsson

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Nagowah, S.D., Rajarai, K., Lallmahamood, M.M.N. (2019). A Hybrid Approach for Recommender Systems in a Proximity Based Social Network. In: Fleming, P., Lacquet, B., Sanei, S., Deb, K., Jakobsson, A. (eds) Smart and Sustainable Engineering for Next Generation Applications. ELECOM 2018. Lecture Notes in Electrical Engineering, vol 561. Springer, Cham. https://doi.org/10.1007/978-3-030-18240-3_28

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  • DOI: https://doi.org/10.1007/978-3-030-18240-3_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-18239-7

  • Online ISBN: 978-3-030-18240-3

  • eBook Packages: EngineeringEngineering (R0)

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