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Planning-Context Aware Mobile Recommendations

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New Trends in Networking, Computing, E-learning, Systems Sciences, and Engineering

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 312))

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Abstract

In the realm of mobile applications a significant effort has been made to develop recommender systems that customize results based off of one’s current location and more recently even their inferred current activity. While this aspect of context has been shown to be quite successful, we suggest anticipating what they are currently planning for the future may help further improve the relevancy of the results as well. This work examines this problem as one of trying to predict the user’s planning context, defined as what activities are currently being planned and how far in the future the event they are planning is going to be. An empirical analysis is made of the predictability of planning context and a discussion of the potential implications of this for mobile context aware recommenders.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Central Connecticut State University, New Britain, CT, USA

    Chad A. Williams

  2. Department of Geography and Environmental Studies, Wilfrid Laurier University, Waterloo, ON, Canada

    Sean T. Doherty

Authors
  1. Chad A. Williams
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  2. Sean T. Doherty
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Correspondence to Chad A. Williams .

Editor information

Editors and Affiliations

  1. Computer Science and Engineering, University of Bridgeport Associate Dean for Graduate Programs, Bridgeport, Connecticut, USA

    Khaled Elleithy

  2. Engineering and Computer Science, University of Bridgeport Dean of the School of Engineering, Bridgeport, Connecticut, USA

    Tarek Sobh

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© 2015 Springer International Publishing Switzerland

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Williams, C.A., Doherty, S.T. (2015). Planning-Context Aware Mobile Recommendations. In: Elleithy, K., Sobh, T. (eds) New Trends in Networking, Computing, E-learning, Systems Sciences, and Engineering. Lecture Notes in Electrical Engineering, vol 312. Springer, Cham. https://doi.org/10.1007/978-3-319-06764-3_2

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  • DOI: https://doi.org/10.1007/978-3-319-06764-3_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-06763-6

  • Online ISBN: 978-3-319-06764-3

  • eBook Packages: EngineeringEngineering (R0)

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