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Reader’s Choice

A Recommendation Platform

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Database Systems for Advanced Applications (DASFAA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10179))

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Abstract

The majority of book sellers usually abstains from offering books that are of too little interest to potential customers. Thence, such sellers might face profit losses, because the product popularity can vary from place to place. In order to avoid these losses, this disquisition introduces Reader’s Choice – a system that recommends sellers to offer books based on the interest of people in different locations. Generally, most residents in a proximity share similar interests. In accordance with the search trends, Reader’s Choice can learn and output the vogue of books in various regions. Thereby, the searches and purchases help Reader’s Choice to determine where books are frequently sought respectively bought. Accordingly, Reader’s Choice can suggest products in regions where they were more often searched and merchandised. Basically, Reader’s Choice analyzes trends in datasets to draw insights. It employs Hadoop for the storage and analysis of search results and deals. A prudent performance scrutiny has testified Reader’s Choice for the best functionality and the second-best information retrieval metrics among competitive book recommendation systems.

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Acknowledgments

Many thanks to Bettina Baumgartner from the University of Vienna for proofreading this paper!

Author information

Authors and Affiliations

  1. KIIT University, Bhubaneswar, Odisha, India

    Sayar Kumar Dey

  2. University of Hagen, Hagen, North Rhine-Westphalia, Germany

    Günter Fahrnberger

Authors
  1. Sayar Kumar Dey
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  2. Günter Fahrnberger
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Corresponding author

Correspondence to Günter Fahrnberger .

Editor information

Editors and Affiliations

  1. Royal Melbourne Institute of Technology , Melbourne, Australia

    Zhifeng Bao

  2. Northwestern University , Evanston, Illinois, USA

    Goce Trajcevski

  3. University of New South Wales , Sydney, New South Wales, Australia

    Lijun Chang

  4. The University of Queensland , Brisbane, Queensland, Australia

    Wen Hua

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Dey, S.K., Fahrnberger, G. (2017). Reader’s Choice. In: Bao, Z., Trajcevski, G., Chang, L., Hua, W. (eds) Database Systems for Advanced Applications. DASFAA 2017. Lecture Notes in Computer Science(), vol 10179. Springer, Cham. https://doi.org/10.1007/978-3-319-55705-2_19

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  • DOI: https://doi.org/10.1007/978-3-319-55705-2_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-55704-5

  • Online ISBN: 978-3-319-55705-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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