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Finding Top-\(k\) Places for Group Social Activities

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Web Technologies and Applications (APWeb 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9865))

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Abstract

Geo-social network applications utilize check-in information to suggest places for social activities. This paper focuses on recommending points of interest (POIs) to groups of users based on the current location of users and the popularity and suitability of the POIs from history. To address the problem, we propose a new type of query, namely, group-based geo-social top-k places (\({\textsf {G}}k{\textsf {P}}\)) query, which takes spatial proximity and social fitness into consideration. This is among the first attempts, and we present the preliminary results. In particular, we investigate the problem formulation, especially the modeling of spatial proximity and social fitness. Two baseline algorithms, distance-driven and relevance-driven, respectively, are conceived. Initial empirical results confirm that \({\textsf {G}}k{\textsf {P}}\) queries meet the needs of potential applications, and the proposed algorithms are sufficient to handle \({\textsf {G}}k{\textsf {P}}\) queries.

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Notes

  1. 1.

    We implemented priority queues with min heaps such that the smaller the priority of an element, the higher it is ranked.

  2. 2.

    http://snap.stanford.edu/data/loc-brightkite.html.

  3. 3.

    http://snap.stanford.edu/data/loc-gowalla.html.

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Acknowledgement

This work was in part supported by NSFC Nos. 61402494 and 61402498, NSF of Hunan No. 2015JJ4009.

Author information

Authors and Affiliations

  1. National University of Defense Technology, Changsha, China

    Xiaosheng Feng, Hao Xu & Xiang Zhao

  2. Pivotal Inc., San Francisco, USA

    Nikos Armenatzoglou

  3. Collaborative Innovation Center of Geospatial Technology, Wuhan, China

    Xiang Zhao

  4. Hong Kong University of Science and Technology, Hong Kong, China

    Pan Hui

Authors
  1. Xiaosheng Feng
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  2. Nikos Armenatzoglou
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  3. Hao Xu
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  4. Xiang Zhao
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  5. Pan Hui
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Corresponding author

Correspondence to Xiaosheng Feng .

Editor information

Editors and Affiliations

  1. University of Tsukuba , Tsukuba, Japan

    Atsuyuki Morishima

  2. East China Normal University , Shanghai, China

    Rong Zhang

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

    Wenjie Zhang

  4. The University of New South Wales, School of Computer Science and Engineering, Sydney, Australia

    Lijun Chang

  5. Advanced Digital Sciences Center, Illinois at Singapore Pte Ltd, Advanced Digital Sciences Center, Fusionopolies Way, Singapore

    Tom Z. J Fu

  6. Hyundai Motor Tower, Pivotal Inc 15/F, Hyundai Motor Tower, Chaoyang, China

    Kuien Liu

  7. Illinois at Singapore Pte Ltd, Advanced Digital Sciences Center , Singapore, Singapore

    Xiaoyan Yang

  8. South China Normal University, School of Computer Science, Guangzhou, China

    Jia Zhu

  9. Department of Computer Science, Hong Kong Baptist University Department of Computer Science, Kowloon Tong, Hong Kong

    Zhiwei Zhang

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Feng, X., Armenatzoglou, N., Xu, H., Zhao, X., Hui, P. (2016). Finding Top-\(k\) Places for Group Social Activities. In: Morishima, A., et al. Web Technologies and Applications. APWeb 2016. Lecture Notes in Computer Science(), vol 9865. Springer, Cham. https://doi.org/10.1007/978-3-319-45835-9_17

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  • DOI: https://doi.org/10.1007/978-3-319-45835-9_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-45834-2

  • Online ISBN: 978-3-319-45835-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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