JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2016, Vol. 51 ›› Issue (7): 30-34.doi: 10.6040/j.issn.1671-9352.1.2015.085

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Construction of expert relationship network based on random walk strategy

  

  1. School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, Yunnan, China
  • Received:2015-11-14 Online:2016-07-20 Published:2016-07-27

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Abstract: Organizing expert relationship is the core of constructing expert relationship network. A method was proposed to build an expert relationship network based on random walk strategy. Firstly, on the basis of the extracted expert entities and their relationships, the method gets a friend relationship, or a guidance relationship or a colleague relationship between two expert entities to form a simple undirected graph. From the relationships between expert nodes in these graphs, an expert relationship matrix was built. Then according to random walk strategy thought, it is made an organic combination of these simple undirected graphs which characterize expert relationships to construct a complex network of expert relationships. The experimental results show that the proposed method to construct an expert relationship network based on random walk strategy is effective.

Key words: expert relationship network, random walk, expert relationship matrix, undirected graph

CLC Number: 

  • TP393
[1] ZHANG J, ACKERMAN M S, ADAMIC L. Expertise networks in online communities: structure and algorithms[C] //Proceedings of the 16th International Conference on WWW. New York: ACM, 2007: 221-230.
[2] ZHANG J, ACKERMAN M, ADMIC L. Community net simulartor: using simulation to study online community network formation and implications [C] //Proceedings of the third Conference on Communities and Technologies. New York: ACM, 2007: 28-38.
[3] CHEN Haiqiang, SHEN Huawei, XIONG Jin, et al. Social network structure behind the mailing lists: ict-iis at trec 2006 expert finding track[C] //Proceedings of 15th Text REtrieval Conference(TREC2006). New York: ACM, 2006.
[4] ZHANG Jing, TANG Jie, LI Junzi. Expert finding in a socail network[J]. Lecture Notes in Computer Science, 2007, 4443:1066-1069.
[5] TANG Jie, ZHANG Jing, YAO Limin, et al. ArnetMiner: extraction and mining of academic social networks[C] //Proceedings of the 15 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York: ACM, 2008: 990-998.
[6] JASCH F, BLUMEN A. Target problem on small-world networks[J]. Physical Review E Statistical Nonlinear and Soft Matter Physics, 2001, 63(4Pt1): 278-300.
[7] SCALA A, AMARAL L A N, BARTHÉLÉMY M. Small-world networks and the conformation space of a short lattice polymer chain[J]. Europhysics Letters, 2001, 55(4): 594-600.
[8] PANDIT S A, AMRITKAR R E. Random spread on the family of small-world networks[J]. Physical Review E Statistical Nonlinear and Soft Matter Physics, 2000, 63(1): 278-300.
[9] LAHTINEN J, KERTESZ J, KASKI K. Random spreading phenomena in annealed small world networks[J]. Physica A: Statistical Mechanics and its Applications, 2002, 311(3): 571-580.
[10] ADAMIC L A, LUKOSE R M, PUNIYANI A R, et al. Search in power-law networks[J]. Physical Review E Statistical Nonlinear and Soft Matter Physics, 2001, 64(4 Pt 2):1515-1523.
[11] NOH J D, RIEGER H. Random walks on complex networks [J]. Physical Review Letters, 2003, 92(11): 87-93.
[12] TADIC B. Exploring complex graphs by random walks[J]. Modeling of Complex Systems: Seventh Granada Lecture, 2003, 661(1):24-27.
[13] HUGHES B D. Random walks and random environments[M]. USA: Oxford University Press, 1996.
[14] 毛存礼,余正涛,吴则建,等.专家证据文档识别无向图模型[J].软件学报,2014,24(11):2734-2746. MAO Cunli, YU Zhengtao, WU Zejian, et al. An undirected graph model for expert evidence document identification[J]. Journal of Software, 2014, 24(11):2734-2746.
[15] PAN Xiao, SHEN Tao, YU Zhengtao, et al. Multi-page Chinese expert metadata extraction method based on the 3d model[J]. Journal of Computational Information System, 2013, 9(6):2251-2259.
[16] JIANG Jin, YAN Xin, YU Zhengtao, et al. A Chinese expert disambiguation method based on semi-supervised graph clustering[J]. International Journal of Machine Learning and Cybernetics, 2014, 5(1):1-8.
[1] FEI Shi-long, BAI Yao-qian. A class of random walks in a random environment with singular jumps [J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2015, 50(11): 119-126.
[2] REN Min1,2, ZHANG Guang-hui1. Absorbing probabilities of random walks in an independent random  environment convergence in distribution on the half-line [J]. J4, 2013, 48(1): 93-99.
[3] WANG Yao. Theoretical analysis and numerical simulation of random walk under sinusoidal force field [J]. J4, 2010, 45(9): 74-78.
[4] LI Cheng-jiang . A new algorithm to find the k shortest paths [J]. J4, 2006, 41(4): 40-43 .
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