Collaboration Prediction in Heterogeneous Information Networks

被引:1
作者
Zhang, Shuhong [1 ]
Xia, Feng [1 ]
Zhang, Jun [1 ]
Bai, Xiaomei [1 ]
Ning, Zhaolong [1 ,2 ]
机构
[1] Dalian Univ Technol, Sch Software, Dalian 116620, Peoples R China
[2] Nanjing Univ, State Key Lab Novel Software Technol, Nanjing 210093, Jiangsu, Peoples R China
来源
2015 IEEE INTERNATIONAL CONFERENCE ON SMART CITY/SOCIALCOM/SUSTAINCOM (SMARTCITY) | 2015年
基金
中国国家自然科学基金;
关键词
collaboration prediction; meta path; heterogeneous information network;
D O I
10.1109/SmartCity.2015.71
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
To reveal the information hiding in the scholarly big data, relationship analysis among academic entities has been studied from different perspectives in recent years. In this paper, we focus on the problem of collaboration relationship prediction between authors in heterogeneous information networks, and a new method called MACP, i.e., Meta path and author Attribute based Collaboration Prediction model, is proposed to solve this problem. We use a two-phase collaboration probability learning approach. First, topological features with author attributes are extracted from the network, and then a supervised learning algorithm is employed to find the best weight associated with each feature to determine the collaboration relationship. We present the experiments on a real information network, namely the APS network, which shows that our proposed model can generate more accurate results compared with the method only considering structural features.
引用
收藏
页码:203 / 208
页数:6
相关论文
共 11 条
[1]  
[Anonymous], P ADV NEUR INF PROC
[2]  
[Anonymous], 2012, P ACM INT C WEB SEAR
[3]  
Chen Luo, 2014, Advances in Information Retrieval. 36th European Conference on IR Research, ECIR 2014. Proceedings: LNCS 8416, P210, DOI 10.1007/978-3-319-06028-6_18
[4]  
He JZ, 2014, LECT NOTES COMPUT SC, V8422, P141, DOI 10.1007/978-3-319-05813-9_10
[5]  
Li N, 2012, INT CONF COMP SCI ED, P1115, DOI 10.1109/ICCSE.2012.6295261
[6]   The link-prediction problem for social networks [J].
Liben-Nowell, David ;
Kleinberg, Jon .
JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY, 2007, 58 (07) :1019-1031
[7]  
Lichtenwalter R. N., 2010, P 16 ACM SIGKDD INT, P243, DOI 10.1145/1835804.1835837
[8]  
Shi C., 2012, Proceedings of the 15th International Conference on Extending Database Technology, P180
[9]   Co-Author Relationship Prediction in Heterogeneous Bibliographic Networks [J].
Sun, Yizhou ;
Barber, Rick ;
Gupta, Manish ;
Aggarwal, Charu C. ;
Han, Jiawei .
2011 INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING (ASONAM 2011), 2011, :121-128
[10]  
Sunt YZ, 2011, PROC VLDB ENDOW, V4, P992