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A Graph Embedding Based Real-Time Social Event Matching Model for EBSNs Recommendation

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Abstract

Event-based social networks (EBSNs), are platforms that provide users with event scheduling and publishing. In recent years, the number of users and events on such platforms has increased dramatically, and interactions have become more complicated, which has made modeling heterogeneous networks more difficult. Moreover, the requirement of real-time matching between users and events becomes urgent because of the significant dynamics brought by the widespread use of mobile devices on such platforms. Therefore, we proposed a graph embedding based real-time social event matching model called GERM. We first model heterogeneous EBSNs into heterogeneous graphs, and use graph embedding technology to represent the nodes and their relationships in the graph which can more effectively reflect the hidden features of nodes and mine user preferences. Then a real-time social event matching algorithm is proposed, which matches users and events on the premise of fully considering user preferences and spatio-temporal characteristics, and recommends suitable events to users in real-time efficiently. We conducted experiments on the Meetup dataset to verify the effectiveness of our method by comparison with the mainstream algorithms. The results show that the proposed algorithm has a good improvement on the matching success rate, user satisfaction, and user waiting time.

Supported by the National Key R&D Program of China (Grant No. 2019YFB1405302), the NSFC (Grant No. 61872072 and No. 61672144), and the State Key Laboratory of Computer Software New Technology Open Project Fund (Grant No. KFKT2018B05).

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References

  1. Chen, L., Liu, C., Liao, K., Li, J., Zhou, R.: Contextual community search over large social networks. In: 2019 IEEE 35th International Conference on Data Engineering (ICDE) (2019)

    Google Scholar 

  2. Chen, L., Liu, C., Zhou, R., Li, J., Wang, B.: Maximum co-located community search in large scale social networks. Proc. VLDB Endow.11, 1233–1246 (2018)

    Article  Google Scholar 

  3. Chen, L., Liu, C., Zhou, R., Xu, J., Li, J.: Finding effective geo-social group for impromptu activity with multiple demands (2019)

    Google Scholar 

  4. Cheng, Y., Yuan, Y., Chen, L., Giraudcarrier, C., Wang, G.: Complex event-participant planning and its incremental variant, pp. 859–870 (2017)

    Google Scholar 

  5. Dong, C., Shen, Y., Zhou, B., Jin, H.: I\(^2\)Rec: an iterative and interactive recommendation system for event-based social networks, pp. 250–261 (2016)

    Google Scholar 

  6. Gao, L., Wu, J., Qiao, Z., Zhou, C., Yang, H., Hu, Y.: Collaborative social group influence for event recommendation, pp. 1941–1944 (2016)

    Google Scholar 

  7. Li, B., Bang, W., Mo, Y., Yang, L.T.: A novel random walk and scale control method for event recommendation. In: 2016 International IEEE Conferences on Ubiquitous Intelligence & Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People, and Smart World Congress (UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld) (2016)

    Google Scholar 

  8. Liu, S., Bang, W., Xu, M.: Event recommendation based on graph random walking and history preference reranking. In: International ACM SIGIR Conference (2017)

    Google Scholar 

  9. Liu, X., He, Q., Tian, Y., Lee, W., Mcpherson, J., Han, J.: Event-based social networks: linking the online and offline social worlds, pp. 1032–1040 (2012)

    Google Scholar 

  10. Macedo, A.Q.D., Marinho, L.B.: Event recommendation in event-based social networks. In: 1st International Workshop on Social Personalisation (SP 2014) (2014)

    Google Scholar 

  11. Mikolov, T., Chen, K., Corrado, G.S., Dean, J.: Efficient estimation of word representations in vector space (2013)

    Google Scholar 

  12. Mo, Y., Li, B., Bang, W., Yang, L.T., Xu, M.: Event recommendation in social networks based on reverse random walk and participant scale control. Future Gener. Comput. Syst.79(PT.1), 383–395 (2018)

    Article  Google Scholar 

  13. Pham, T.A.N., Li, X., Gao, C., Zhang, Z.: A general graph-based model for recommendation in event-based social networks. In: 2015 IEEE 31st International Conference on Data Engineering (2015)

    Google Scholar 

  14. Qiao, Z., Zhang, P., Cao, Y., Zhou, C., Guo, L., Fang, B.: Combining heterogenous social and geographical information for event recommendation, pp. 145–151 (2014)

    Google Scholar 

  15. She, J., Tong, Y., Chen, L.: Utility-aware social event-participant planning, pp. 1629–1643 (2015)

    Google Scholar 

  16. Sun, Y., Han, J., Yan, X., Yu, P.S., Wu, T.: Pathsim: meta path-based top-k similarity search in heterogeneous information networks. Proc. VLDB Endow.4(11), 992–1003 (2011)

    Article  Google Scholar 

  17. Sun, Y., Norick, B., Han, J., Yan, X., Yu, P.S., Yu, X.: Pathselclus: integrating meta-path selection with user-guided object clustering in heterogeneous information networks. ACM Trans. Knowl. Discov. Data7(3), 11 (2013)

    Article  Google Scholar 

  18. Swami, A., Jain, R.: Scikit-learn: machine learning in python. J. Mach. Learn. Res.12(10), 2825–2830 (2012)

    MathSciNet  Google Scholar 

  19. Tong, Y., Meng, R., She, J.: On bottleneck-aware arrangement for event-based social networks, pp. 216–223 (2015)

    Google Scholar 

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Authors and Affiliations

  1. Northeastern University, Shenyang, China

    Gang Wu, Xueyu Li, Kaiqian Cui, Zhiyong Chen, Baiyou Qiao, Donghong Han & Li Xia

  2. State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China

    Gang Wu

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  1. Gang Wu

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  2. Xueyu Li

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  3. Kaiqian Cui

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  4. Zhiyong Chen

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  5. Baiyou Qiao

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  6. Donghong Han

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  7. Li Xia

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Corresponding author

Correspondence toGang Wu.

Editor information

Editors and Affiliations

  1. VU Amsterdam, Amsterdam, The Netherlands

    Zhisheng Huang

  2. VU Amsterdam, Amsterdam, The Netherlands

    Wouter Beek

  3. Victoria University, Melbourne, VIC, Australia

    Hua Wang

  4. Swinburne University of Technology, Hawthorn, VIC, Australia

    Rui Zhou

  5. Victoria University, Melbourne, VIC, Australia

    Yanchun Zhang

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Wu, G.et al. (2020). A Graph Embedding Based Real-Time Social Event Matching Model for EBSNs Recommendation. In: Huang, Z., Beek, W., Wang, H., Zhou, R., Zhang, Y. (eds) Web Information Systems Engineering – WISE 2020. WISE 2020. Lecture Notes in Computer Science(), vol 12342. Springer, Cham. https://doi.org/10.1007/978-3-030-62005-9_4

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