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A new point-of-interest group recommendation method in location-based social networks

  • S.I. : Deep Social Computing
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Abstract

POI group recommendation is one of the hottest research topics in location-based social networks, which recommends the most agreeable places for a group of users. However, traditional POI group recommendation methods only generate a consensus function to aggregate individual preference into group preference and they do not consider all the factors that can determine the results of POI group recommendation, which leads to a low recommendation accuracy. What’s more, these methods have a long running time. Therefore, in this paper, we propose a new POI group recommendation method with an extreme learning machine (ELM) called PGR-ELM. The PGR-ELM method regards POI group recommendation as a binary classification problem. First, three features are extracted from three factors: POI popularity, group members’ distance to POI, members’ interest preferences combined affinity between group members. These features simultaneously consider all the factors that can determine the results of recommendation and guarantee the effectiveness of POI group recommendation. Then, the extracted features are input to train an ELM classifier because of its fast learning speed, which guarantees the efficiency of POI group recommendation. Finally, extensive experiments verify the accuracy and efficiency of PGR-ELM method.

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Acknowledgements

This research is partially supported by the National Natural Science Foundation of China under Grant Nos. 61672145, 61702086, China Postdoctoral Science Foundation under Grant No. 2018M631806, Natural Science Foundation of Liaoning Province of China under Grant No. 20180550260, Scientific Research Foundation of Liaoning Province under Grant Nos. L2019 001, L2019003, Doctoral Business and Innavation Launching Plan of Yingkou City under Grant No. QB-2019-16.

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Authors and Affiliations

  1. College of Computer Science and Engineering, Northeastern University, Liaoning, 110819, Shenyang, China

    Xiangguo Zhao & Yongjiao Sun

  2. College of Electrical Engineering, Yingkou Institute of Technology, Yingkou, 115014, Liaoning, China

    Zhen Zhang

  3. Key Laboratory of Ministry of Education on Safe Mining of Deep Metal Mines, Northeastern University, Shenyang, China

    Xin Bi

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  1. Xiangguo Zhao
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  2. Zhen Zhang
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Correspondence to Xiangguo Zhao.

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Zhao, X., Zhang, Z., Bi, X. et al. A new point-of-interest group recommendation method in location-based social networks. Neural Comput & Applic 35, 12945–12956 (2023). https://doi.org/10.1007/s00521-020-04979-4

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