logo

SCIENCE CHINA Information Sciences, Volume 63 , Issue 4 : 149101(2020) https://doi.org/10.1007/s11432-017-9701-0

Inferring explicit and implicit social ties simultaneously in mobile social networks

More info
  • ReceivedFeb 12, 2018
  • AcceptedOct 31, 2018
  • PublishedMar 6, 2020

Abstract

There is no abstract available for this article.


Acknowledgment

This work was supported by National Natural Science Foundation of China (Grant Nos. 61876006, 61572041).


Supplement

Appendixes A–E.


References

[1] Eagle N, Pentland A, Lazer D. From the Cover: Inferring friendship network structure by using mobile phone data. Proc Natl Acad Sci USA, 2009, 106: 15274-15278 CrossRef PubMed ADS Google Scholar

[2] Wang D S, Pedreschi D, Song C M, et al. Human mobility, social ties, and link prediction. In: Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011. 1100--1108. Google Scholar

[3] Qin T, Shangguan W, Song G. Spatio-Temporal Routine Mining on Mobile Phone Data. ACM Trans Knowl Discov Data, 2018, 12: 1-24 CrossRef Google Scholar

[4] Tang J, Lou T C, Kleinberg J. Inferring social ties across heterogenous networks. In: Proceedings of the 5th ACM International Conference on Web Search and Data Mining, 2012. 743--752. Google Scholar

[5] Tang W B, Zhuang H L, Tang J. Learning to infer social ties in large networks. In: Proceedings of Joint European Conference on Machine Learning and Knowledge Discovery in Databases, Berlin, 2011. 381--397. Google Scholar

[6] Qin Y, Yu Z, Wang Y. Detecting micro-blog user interest communities through the integration of explicit user relationship and implicit topic relations. Sci China Inf Sci, 2017, 60: 092105 CrossRef Google Scholar

[7] Krebs V E. Mapping networks of terrorist cells. Connections, 2002, 24: 43--52. Google Scholar

[8] Taheri S M, Mahyar H, Firouzi M, et al. Extracting implicit social relation for social recommendation techniques in user rating prediction. In: Proceedings of the 26th International Conference on World Wide Web Companion, 2017. 1343--1351. Google Scholar

  • Table 1   Results of explicit and implicit tie recognition
    ModelFamilyColleague
    Precision Recall F1-score Precision Recall F1-score
    ExplicitLogistic regression 0.8494 0.4619 0.5984 0.9032 0.2500 0.3916
    Classification and regression trees 0.8992 0.6783 0.7733 0.9285 0.4062 0.5652
    PLP-FGM 0.6682 0.8033 0.7296 0.9527 0.8129 0.8773
    Factor graph 0.7064 0.8651 0.7778 0.9553 0.8117 0.8777
    Community factor graph 0.8418 0.9269 0.8823 0.9693 0.9278 0.9481
    ImplicitLogistic regression 0.8571 0.0517 0.0976 0.8727 0.0250 0.0486
    Classification and regression trees 1 0.1121 0.2016 0.9955 0.0244 0.0477
    Multilayer perception 0.4327 0.1940 0.2679 0.5020 0.0010 0.0021
    Community factor graph 0.5192 0.5198 0.5195 0.5491 0.5912 0.5694

Copyright 2020 Science China Press Co., Ltd. 《中国科学》杂志社有限责任公司 版权所有

京ICP备17057255号       京公网安备11010102003388号