Academic Collaborator Recommendation Based on Attributed Network Embedding

Purpose:Based on real-world academic data,this study aims to use network embedding technology to mining academic relationships,and investigate the effectiveness of the proposed embedding model on academic collaborator recommendation tasks.Design/methodology/approach:We propose an academic collaborator recommendation model based on attributed network embedding(ACR-ANE),which can get enhanced scholar embedding and take full advantage of the topological structure of the network and multi-type scholar attributes.The non-local neighbors for scholars are defined to capture strong relationships among scholars.A deep auto-encoder is adopted to encode the academic collaboration network structure and scholar attributes into a low-dimensional representation space.Findings:1.The proposed non-local neighbors can better describe the relationships among scholars in the real world than the first-order neighbors.2.It is important to consider the structure of the academic collaboration network and scholar attributes when recommending collaborators for scholars simultaneously.Research limitations:The designed method works for static networks,without taking account of the network dynamics.Practical implications:The designed model is embedded in academic collaboration network structure and scholarly attributes,which can be used to help scholars recommend potential collaborators.Originality/value:Experiments on two real-world scholarly datasets,Aminer and APS,show that our proposed method performs better than other baselines.

人际关系对学术型硕士生学术化的影响研究

学术化是衡量研究生教育质量的重要指标。本文基于我国“双一流”建设高校学术型硕士生的实证调查数据,探讨硕士生学术化的现状以及各类人际关系对学术化的影响。研究发现,我国学术型硕士生学术化整体处于中等偏上水平,通用能力和社会成熟方面的表现均要优于学术能力和学术热情方面的表现。性别差异存在于学术热情和社会成熟上,学科差异存在于学术热情上,户籍差异存在于社会成熟上,地区和年级差异存在于学术能力、通用能力及社会成熟上。导学关系正向预测学术能力、通用能力和学术热情;同伴关系正向预测通用能力和社会成熟;亲子关系仅正向预测学术能力;校外学术团体关系正向预测学术能力和学术热情,但负向影响社会成熟。因此,应注重硕士生学术化各维度的综合发展,关注群体差异,兼顾校内外重要他人的影响。