TY - GEN
T1 - TNERec
T2 - 4th IEEE SmartWorld, 15th IEEE International Conference on Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018
AU - Kong, Xiangjie
AU - Mao, Mengyi
AU - Liu, Jiaying
AU - Xu, Bo
AU - Huang, Ruihe
AU - Jin, Qun
N1 - Funding Information:
This work was partially supported by the Fund for Promoting the Reform of Higher Education by Using Big Data Technology, Energizing Teachersand Students to Explore the Future (2017A01002), and the Fundamental Research Funds for the Central Universities (DUT18JC09).
Publisher Copyright:
© 2018 IEEE.
PY - 2018/12/4
Y1 - 2018/12/4
N2 - Collaboration is increasingly becoming a vital factor in an academic network, which can bring lots of benefits for scholars. Ubiquitous intelligence also provides an effective way for scholars to find collaborators. However, due to the large-scale of scholarly big data, there is a lot of information hard to capture in networks and we need to dig out valid information from collaboration networks. It is a valuable and urgent task to find appropriate collaborators for scholars. To address these problems, we hypothesize that fusing topic model and structure information could improve the performance of recommendations. In this paper, we propose a collaborator recommendation system, named TNERec (Topic-aware Network Embedding for scientific collaborator Recommendation), learning representations from scholars' research interests and network structure. TNERec first extracts scholars' research interests based on topic model and then learns vectors of scholars with network embedding. Finally, top-k recommendation list is generated based on the scholar vectors. Experimental results on a real-world dataset show the effectiveness of the proposed framework compared with state-of-the-art collaboration recommendation baselines.
AB - Collaboration is increasingly becoming a vital factor in an academic network, which can bring lots of benefits for scholars. Ubiquitous intelligence also provides an effective way for scholars to find collaborators. However, due to the large-scale of scholarly big data, there is a lot of information hard to capture in networks and we need to dig out valid information from collaboration networks. It is a valuable and urgent task to find appropriate collaborators for scholars. To address these problems, we hypothesize that fusing topic model and structure information could improve the performance of recommendations. In this paper, we propose a collaborator recommendation system, named TNERec (Topic-aware Network Embedding for scientific collaborator Recommendation), learning representations from scholars' research interests and network structure. TNERec first extracts scholars' research interests based on topic model and then learns vectors of scholars with network embedding. Finally, top-k recommendation list is generated based on the scholar vectors. Experimental results on a real-world dataset show the effectiveness of the proposed framework compared with state-of-the-art collaboration recommendation baselines.
KW - Collaborator Recommendation
KW - Network Embedding
KW - Topic Modeling
UR - http://www.scopus.com/inward/record.url?scp=85060303004&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85060303004&partnerID=8YFLogxK
U2 - 10.1109/SmartWorld.2018.00177
DO - 10.1109/SmartWorld.2018.00177
M3 - Conference contribution
AN - SCOPUS:85060303004
T3 - Proceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018
SP - 1007
EP - 1014
BT - Proceedings - 2018 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovations, SmartWorld/UIC/ATC/ScalCom/CBDCom/IoP/SCI 2018
A2 - Loulergue, Frederic
A2 - Wang, Guojun
A2 - Bhuiyan, Md Zakirul Alam
A2 - Ma, Xiaoxing
A2 - Li, Peng
A2 - Roveri, Manuel
A2 - Han, Qi
A2 - Chen, Lei
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 7 October 2018 through 11 October 2018
ER -