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RelRec: A Graph-Based Triggering Object Relationship Recommender System

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Database Systems for Advanced Applications (DASFAA 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7826))

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Abstract

Numerous services (email, motion sensor, etc.) emerge and tend to function more comprehensively. What comes with this is the increasing attention to collaboration between them. For example, IFTTT (IF This Then That) enables people to set triggering relationships between various services to be automatically implemented in the cloud. RelRec is an triggering object relationship recommender system, building a bipartite graph representing the relationships between services. We propose an algorithm to rate relationships by similarity, and diversify the results by a modified classic method from graph theory.

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References

  1. Jambor, T., Wang, J., Lathia, N.: Using control theory for stable and efficient recommender systems. In: Proc. WWW 2012 (2012)

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  2. Adomavicius, G., Kwon, Y.: Maximizing aggregate recommendation diversity: A graph-theoretic approach. In: Proc. DiveRS 2001 (2001)

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  3. Sarwar, B., Karypis, G., Konstan, J., Riedl, J.: Item-based collaborative filtering recommendation algorithms. In: Proc. WWW 2001 (2001)

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Author information

Authors and Affiliations

  1. Institute of Massive Computing, East China Normal University, China

    Yuwen Dai, Guangyao Li & Ruoyu Li

Authors
  1. Yuwen Dai
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  2. Guangyao Li
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  3. Ruoyu Li
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Binghamton University, 13902, Binghamton, NY, USA

    Weiyi Meng

  2. Department of Computer Science and Technology, Tsinghua University, 100084, Beijing, China

    Ling Feng

  3. Department of Computer Science, National University of Singapore, 117417, Singapore

    Stéphane Bressan

  4. Research Group Data Analystics and Computing, University of Vienna, 1090, Vienna, Austria

    Werner Winiwarter

  5. School of Computer, Wuhan University, 430072, Wuhan, China

    Wei Song

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© 2013 Springer-Verlag Berlin Heidelberg

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Dai, Y., Li, G., Li, R. (2013). RelRec: A Graph-Based Triggering Object Relationship Recommender System. In: Meng, W., Feng, L., Bressan, S., Winiwarter, W., Song, W. (eds) Database Systems for Advanced Applications. DASFAA 2013. Lecture Notes in Computer Science, vol 7826. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37450-0_39

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  • DOI: https://doi.org/10.1007/978-3-642-37450-0_39

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37449-4

  • Online ISBN: 978-3-642-37450-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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