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Using Implicit Preference Relations to Improve Content Based Recommending

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E-Commerce and Web Technologies (EC-Web 2015)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 239))

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Abstract

Our work is generally focused on recommending for small or medium-sized e-commerce portals, where we are facing scarcity of explicit feedback, low user loyalty, short visit times or low number of visited objects. In this paper, we present a novel approach to use specific user behavior as implicit feedback, forming binary relations between objects. Our hypothesis is that if user select some object from the list of displayed objects, it is an expression of his/her binary preference between selected and other shown objects. These relations are expanded based on content-based similarity of objects forming partial ordering of objects. Using these relations, it is possible to alter any list of recommended objects or create one from scratch.

We have conducted several off-line experiments with real user data from a Czech e-commerce site with keyword based VSM and SimCat recommenders. Experiments confirmed competitiveness of our method, however on-line A/B testing should be conducted in the future work.

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Notes

  1. 1.

    Probabilistic sum \( S_{sum} \left( {a,b} \right) = a + b - a*b \) .

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Acknowledgments

This work was supported by the grant SVV-2015-260222, P46 and GAUK-126313. The SQL export of the bookshop dataset used during the experiments can be obtained on http://www.ksi.mff.cuni.cz/~peska/bookshop2014.zip.

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Authors and Affiliations

  1. Faculty of Mathematics and Physics Charles, University in Prague, Malostranske namesti 25, Prague, Czech Republic

    Ladislav Peska & Peter Vojtas

Authors
  1. Ladislav Peska
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  2. Peter Vojtas
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Corresponding author

Correspondence to Ladislav Peska .

Editor information

Editors and Affiliations

  1. Institut für Informatik, B6.26, University of Mannheim Institut für Informatik, B6.26, Mannheim, Germany

    Heiner Stuckenschmidt

  2. Dep. of Computer Science, TU Dortmund Dep. of Computer Science, Dortmund, Germany

    Dietmar Jannach

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Peska, L., Vojtas, P. (2015). Using Implicit Preference Relations to Improve Content Based Recommending. In: Stuckenschmidt, H., Jannach, D. (eds) E-Commerce and Web Technologies. EC-Web 2015. Lecture Notes in Business Information Processing, vol 239. Springer, Cham. https://doi.org/10.1007/978-3-319-27729-5_1

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  • DOI: https://doi.org/10.1007/978-3-319-27729-5_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27728-8

  • Online ISBN: 978-3-319-27729-5

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