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Research collaboration network has become an essential part in our academic activities. We can keep or develop collaboration relationships with other researchers or share research results with them within the research collaboration network. It is well generally accepted that different relationships have essentially different influences on the collaboration of researchers. Such a scenario also happens in our daily life. The advisor-advisee relationship plays an important role in the research collaboration network, so identification of advisor-advisee relationship can benefit the collaboration of researchers. In this paper, we aim to conduct a systematic investigation of the problem of indentifying the social relationship types from publication networks, and try to propose an easily computed and effective solution to this problem. Based on the common knowledge that graduate student always co-authors his papers with his advisor and not vice versa, our study starts with an analysis on publication network, and retrieves these features that can represent the advisor-advisee relationship. According to these features, an advisor-advisee relationship identification algorithm based on maximum entropy model with feature selection is proposed in this paper. We employ the DBLP dataset to test the proposed algorithm. The results show that 1) the mean of deviation of estimated end year to graduation year is 1.39; 2) the accuracy of advisor-advisee relationship identification results is more than 95%, and it is better than those of other algorithms obviously. Finally, the proposed algorithm can be extended to the relationship identification in online social network.
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Keywords:
- social network /
- relationship identification /
- maximum entropy /
- feature selection
[1] Bai M, Hu K, Tang Y 2011 Chin. Phys. B 20 12
[2] Backstrom L, Leskovec J 2011 Proceedings of the 4th ACM International Conference on Web Search and Data Mining Hong Kong, China, February 9-12, 2011 pp635-644
[3] Leskovec J, Huttenlocher D P, Kleinberg J M 2010 Proceedings of 19th International World Wide Web Conference Raleigh, USA, April 26-30, 2010 pp641-650
[4] Diehl C P, Namata G, Getoor L 2007 Proceedings of Twenty-Second Conference on Artificial Intelligence Vancouver, Canada, July 22-26, 2007 pp546-552
[5] Eagle N, Pentland A S, Lazer D 2009 Proc. Nat. Acad. Sci. U. S. A 106 36
[6] Wang C, Han J, Jia Y, Tang J, Zhang D, Yu Y, Guo J 2010 Proceedings of 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining Washington D.C., USA, July 24-28, 2010 pp203-212
[7] Tang J, Lou T, Kleinberg J 2012 Proceedings of the 5th ACM International Conference on Web Search and Data Mining Seattle, USA, February 8-12, 2012 pp743-752
[8] Tang S, Yuan J, Mao X, Li X, Chen W, Dai G 2011 Proceedings of 30th IEEE International Conference on Computer Communications Shanghai, China, April 10-15, 2011 pp1661-1669
[9] Zhang Y Ch, Liu Y, Zhang H F, Cheng H, Xiong F 2012 Acta Phys. Sin. 60 050501(in Chinese) [张彦超, 刘云, 张海峰, 程辉, 熊菲 2012 60 050501]
[10] Gu Y R, Xia L L 2012 Acta Phys. Sin. 61 238701 (in Chinese) [顾亦然, 夏玲玲 2012 61 238701]
[11] Yu H, Liu Z, Li Y J 2013 Acta Phys. Sin. 62 020204 (in Chinese) [于会, 刘尊, 李勇军 2013 62 020204]
[12] Wu T Y, Chen Y G, Han J W 2010 Data Min. Knowl. Disc. 21 3
[13] Byrd R H, Nocedal J, Schnabel R B 1994 Mathematical Programming A, B 63 4
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[1] Bai M, Hu K, Tang Y 2011 Chin. Phys. B 20 12
[2] Backstrom L, Leskovec J 2011 Proceedings of the 4th ACM International Conference on Web Search and Data Mining Hong Kong, China, February 9-12, 2011 pp635-644
[3] Leskovec J, Huttenlocher D P, Kleinberg J M 2010 Proceedings of 19th International World Wide Web Conference Raleigh, USA, April 26-30, 2010 pp641-650
[4] Diehl C P, Namata G, Getoor L 2007 Proceedings of Twenty-Second Conference on Artificial Intelligence Vancouver, Canada, July 22-26, 2007 pp546-552
[5] Eagle N, Pentland A S, Lazer D 2009 Proc. Nat. Acad. Sci. U. S. A 106 36
[6] Wang C, Han J, Jia Y, Tang J, Zhang D, Yu Y, Guo J 2010 Proceedings of 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining Washington D.C., USA, July 24-28, 2010 pp203-212
[7] Tang J, Lou T, Kleinberg J 2012 Proceedings of the 5th ACM International Conference on Web Search and Data Mining Seattle, USA, February 8-12, 2012 pp743-752
[8] Tang S, Yuan J, Mao X, Li X, Chen W, Dai G 2011 Proceedings of 30th IEEE International Conference on Computer Communications Shanghai, China, April 10-15, 2011 pp1661-1669
[9] Zhang Y Ch, Liu Y, Zhang H F, Cheng H, Xiong F 2012 Acta Phys. Sin. 60 050501(in Chinese) [张彦超, 刘云, 张海峰, 程辉, 熊菲 2012 60 050501]
[10] Gu Y R, Xia L L 2012 Acta Phys. Sin. 61 238701 (in Chinese) [顾亦然, 夏玲玲 2012 61 238701]
[11] Yu H, Liu Z, Li Y J 2013 Acta Phys. Sin. 62 020204 (in Chinese) [于会, 刘尊, 李勇军 2013 62 020204]
[12] Wu T Y, Chen Y G, Han J W 2010 Data Min. Knowl. Disc. 21 3
[13] Byrd R H, Nocedal J, Schnabel R B 1994 Mathematical Programming A, B 63 4
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