
Time-series prediction based on global fuzzy measure in social networks
Li-ming YANG, Wei ZHANG, Yun-fang CHEN
Time-series prediction based on global fuzzy measure in social networks
Social network analysis (SNA) is among the hottest topics of current research. Most measurements of SNA methods are certainty oriented, while in reality, the uncertainties in relationships are widely spread to be overridden. In this paper, fuzzy concept is introduced to model the uncertainty, and a similarity metric is used to build a fuzzy relation model among individuals in the social network. The traditional social network is transformed into a fuzzy network by replacing the traditional relations with fuzzy relation and calculating the global fuzzy measure such as network density and centralization. Finally, the trend of fuzzy network evolution is analyzed and predicted with a fuzzy Markov chain. Experimental results demonstrate that the fuzzy network has more superiority than the traditional network in describing the network evolution process.
Time-series network / Fuzzy network / Fuzzy Markov chain
[1] |
Araujo, E., 2008. Social relationship explained by fuzzy logic. Proc. IEEE Int. Conf. on Fuzzy Systems, p.2129−2134. [
CrossRef
Google scholar
|
[2] |
Bastani, S., Jafarabad, A.K., Zarandi, M.H.F., 2013. Fuzzy models for link prediction in social networks. Int. J. Intell. Syst., 28(8): 768−786. [
CrossRef
Google scholar
|
[3] |
Brunelli, M., Fedrizzi, M., 2009. A fuzzy approach to social network analysis. Proc. Int. Conf. on Advances in Social Network Analysis and Mining, p.225−230. [
CrossRef
Google scholar
|
[4] |
Brunelli, M., Fedrizzi, M., Fedrizzi, M., 2014. Fuzzy m-ary adjacency relations in social network analysis: optimization and consensus evaluation. Inform. Fusion, 17: 36−45. [
CrossRef
Google scholar
|
[5] |
de Sa, H.R., Prudencio, R.B.C., 2011. Supervised link prediction in weighted networks. Proc. Int. Conf. on Neural Networks, p.2281−2288. [
CrossRef
Google scholar
|
[6] |
Ebel, H., Davidsen, J., Bornholdt, S., 2002. Dynamics of social networks. Complexity, 8(2): 24−27. [
CrossRef
Google scholar
|
[7] |
Freeman, L.C., 1978. Centrality in social networks conceptual clarification. Soc. Netw., 1(3): 215−239. [
CrossRef
Google scholar
|
[8] |
Freeman, L.C., 2004. The Development of Social Network Analysis: a Study in the Sociology of Science. Empirical Press, Vancouver.
|
[9] |
Hasan, M.A., Chaoji, V., Salem, S.,
|
[10] |
He, Y.L., Liu, J.N.K., Hu, Y.X.,
CrossRef
Google scholar
|
[11] |
Huang, Z., Lin, D.K.J., 2009. The time-series link prediction problem with applications in communication surveillance. INFORMS J. Comput., 21(2): 286−303. [
CrossRef
Google scholar
|
[12] |
Jaccard, P., 1901. étude comparative de la distribution florale dans une portion des alpes et des jura. Bull. Soc. Vaud. Sci. Nat., 37: 547−579 (in French).
|
[13] |
Jin, E.M., Girvan, M., Newman, M.E.J., 2001. The structure of growing social networks. Available from http://ideas.repec.org/p/wop/safiwp/01-06-032.html [Accessed on <month>June</month><day>30</day>, 2015].
|
[14] |
Khorasani, E.S., Rahimi, S., Patel, P.,
CrossRef
Google scholar
|
[15] |
Nair, P.S., Sarasamma, S.T., 2007. Data mining through fuzzy social network analysis. Proc. 26th Annual Meeting of the North American Fuzzy Information Processing Society, p.251−255. [
CrossRef
Google scholar
|
[16] |
Ryoke, M., Nakamori, Y., Suzuki, K., 1995. Adaptive fuzzy clustering and fuzzy prediction models. Proc. Int. Joint Conf. of 4th IEEE Int. Conf. on Fuzzy Systems and 2nd Int. Fuzzy Engineering Symp., p.2215−2220. [
CrossRef
Google scholar
|
[17] |
Yan, B., Gregory, S., 2011. Finding missing edges and communities in incomplete networks. J. Phys. A, 44: 495102.1−495102.15.
|
[18] |
Zadeh, L.A., 1965. Fuzzy sets. Inform. Contr., 8(3): 338−353.
|
[19] |
Zhang, J.Y., Borland, R., Coghill, K., 2011. Evaluating the effect of health warnings in influencing Australian smokers’ psychosocial and quitting behaviours using fuzzy causal network. Expert Syst. Appl., 38(6): 6430−6438. [
CrossRef
Google scholar
|
[20] |
Zhu, J., Xie, Q., Chin, E.J., 2012. A hybrid time-series link prediction framework for large social network. Proc. 23rd Int. Conf. on Database and Expert Systems Applications, p.345−359. [
CrossRef
Google scholar
|
/
〈 |
|
〉 |