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Shifu2: A Network Representation Learning Based Model for Advisor-Advisee Relationship Mining.

Authors :
Liu, Jiaying
Xia, Feng
Wang, Lei
Xu, Bo
Kong, Xiangjie
Tong, Hanghang
King, Irwin
Source :
IEEE Transactions on Knowledge & Data Engineering. Apr2021, Vol. 33 Issue 4, p1763-1777. 15p.
Publication Year :
2021

Abstract

The advisor-advisee relationship represents direct knowledge heritage, and such relationship may not be readily available from academic libraries and search engines. This work aims to discover advisor-advisee relationships hidden behind scientific collaboration networks. For this purpose, we propose a novel model based on Network Representation Learning (NRL), namely Shifu2, which takes the collaboration network as input and the identified advisor-advisee relationship as output. In contrast to existing NRL models, Shifu2 considers not only the network structure but also the semantic information of nodes and edges. Shifu2 encodes nodes and edges into low-dimensional vectors respectively, both of which are then utilized to identify advisor-advisee relationships. Experimental results illustrate improved stability and effectiveness of the proposed model over state-of-the-art methods. In addition, we generate a large-scale academic genealogy dataset by taking advantage of Shifu2. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10414347
Volume :
33
Issue :
4
Database :
Academic Search Index
Journal :
IEEE Transactions on Knowledge & Data Engineering
Publication Type :
Academic Journal
Accession number :
149122329
Full Text :
https://doi.org/10.1109/TKDE.2019.2946825