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International Conference on Analysis of Images, Social Networks and Texts

AIST 2015: Analysis of Images, Social Networks and Texts pp 175–186Cite as

Analysis of the Adaptive Nature of Collaborative Filtering Techniques in Dynamic Environment

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 542))

Abstract

Collaborative filtering (CF) has been an active area of research for a long time. However, most of the works available in the literature either focuses on handling cold start problems (when CF fails to make acceptable prediction due to the lack of ratings) or emphasizes on improving CF performance in terms of some evaluation statistics. Very few of them addressed the problem and issues of updating from a cold start affected initial stage to a steady one. To cope with this progressive nature of CF, we propose to model the entire life cycle of Recommender System (RS). Specifically, we suggest a combination of two neural network based CF techniques for the implementation of a complete RS framework. We propose to adopt the cold start based algorithm proposed by Bobadilla et al. for the initial stage. For the later stage we propose a new algorithm based on neural network. We suggest to adopt these two algorithms in different stages of CF to ensure better performance and uniformity throughout the RS life cycle.

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Authors and Affiliations

  1. Institute of Information Technology, University of Dhaka, Dhaka, Bangladesh

    Khaleda Akhter & Sheikh Muhammad Sarwar

Authors
  1. Khaleda Akhter
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  2. Sheikh Muhammad Sarwar
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Corresponding author

Correspondence to Sheikh Muhammad Sarwar .

Editor information

Editors and Affiliations

  1. Krasovsky Institute of Mathematics and Mechanics, Yekaterinburg, Russia

    Mikhail Yu. Khachay

  2. Wolverhampton, United Kingdom

    Natalia Konstantinova

  3. Technische Universität Darmstadt, Darmstadt, Germany

    Alexander Panchenko

  4. National Research University Higher School of Economics, Moscow, Russia

    Dmitry Ignatov

  5. Ural Federal University, Yekaterinbug, Russia

    Valeri G. Labunets

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© 2015 Springer International Publishing Switzerland

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Akhter, K., Sarwar, S.M. (2015). Analysis of the Adaptive Nature of Collaborative Filtering Techniques in Dynamic Environment. In: Khachay, M., Konstantinova, N., Panchenko, A., Ignatov, D., Labunets, V. (eds) Analysis of Images, Social Networks and Texts. AIST 2015. Communications in Computer and Information Science, vol 542. Springer, Cham. https://doi.org/10.1007/978-3-319-26123-2_17

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  • DOI: https://doi.org/10.1007/978-3-319-26123-2_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26122-5

  • Online ISBN: 978-3-319-26123-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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