融合多特征的属性异质网络嵌入方法  

Method of Attributed Heterogeneous Network Embedding with Multiple Features

作　　者：汤启友 张凤荔[1] 王瑞锦[1] 王雪婷 周志远 韩英军 TANG Qi-you;ZHANG Feng-li;WANG Rui-jin;WANG Xue-ting;ZHOU Zhi-yuan;HAN Ying-jun(School of Information and Software Engineering,University of Electronic Science and Technology of China,Chengdu 610054,China)

机构地区：[1]电子科技大学信息与软件工程学院,成都610054

出　　处：《计算机科学》2022年第12期146-154,共9页Computer Science

基　　金：国家自然科学基金(61802033,61472064,61602096);四川省区域创新合作项目(2020YFQ0018);四川省科技计划重点研发项目(2021YFG0027,2020YFG0475,2018GZ0087,2019YJ0543);博士后基金项目(2018M643453);广东省国家重点实验室项目(2017B030314131);网络与数据安全四川省重点实验室开放课题(NDSMS201606)。

摘　　要：网络嵌入旨在用低维、实值的向量表示非结构化网络中的节点,使节点嵌入尽可能地保留原始网络中的结构特征与属性特征。然而,当前研究主要集中于嵌入网络结构,对异质信息网络中具有丰富语义的关系属性和节点属性考虑得较少,可能导致节点嵌入语义缺失,从而影响下游应用的预测效果。针对该问题,设计了一种融合多特征的属性异质网络嵌入(Attributed Heterogeneous Network Embedding with Multiple Features,MFAHNE)方法。该方法通过序列采样、结构特征嵌入、属性特征嵌入、特征融合等步骤将网络中的关系属性、节点属性、结构语义等特征融合至最终节点嵌入。实验结果表明,该方法能兼顾结构特征与属性特征,实现两种特征信息的相互补充,优于传统的网络嵌入方法。Network embedding aims to represent nodes in unstructured network with low-dimensional,real-valued vectors,so that node embedding can retain the structural and attribute features of the original network as much as possible.However,current research mainly focuses on embedding the network structure.There are few researches considering relationship attributes and node attributes with rich semantics in heterogeneous information networks,which mayresult in semetic loss of node embedding and affect the prediction effect of downstream applications.To solve this problem,this paper designs a method of attributed heteroge-neous network embedding with multiple features(MFAHNE).This method integrates the relationship attributes,node attributes and structural semantics in the network into the final node embedding through the steps of sampling sequence,embedding with structural feature,embedding with attribute feature and merging features.Experiment result shows that this method can take into account the structural feature and attribute features,realizes the mutual supplement of two kinds of feature information,and is better than the traditional network embedding methods.

关 键 词：网络嵌入 异质信息网络 结构特征 属性特征 属性异质网络 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]