计算机工程

• 人工智能及识别技术 • 上一篇    下一篇

异质信息网络中演员合作关系的链路预测

郭振宏,李海峰   

  1. (中央财经大学 信息学院,北京 100081)
  • 收稿日期:2015-12-28 出版日期:2017-01-15 发布日期:2017-01-13
  • 作者简介:郭振宏(1989—),女,硕士研究生,主研方向为数据挖掘、链路预测;李海峰,副教授。
  • 基金项目:
    国家自然科学基金(61100112,61309030);国家社会科学基金重点项目(13AXW010);北京市青年英才计划项目(YETP0987);中央财经大学“121”青年人才发展基金(QBJ1427)。

Link Prediction of Actor Cooperation Relationship in Heterogeneous Information Network

GUO Zhenhong,LI Haifeng   

  1. (School of Information,Central University of Finance and Economics,Beijing 100081,China)
  • Received:2015-12-28 Online:2017-01-15 Published:2017-01-13

摘要: 在异质信息网络中,节点与链接的异质特性和复杂性会增加链路预测的难度。针对该问题,提出一种采用综合拓扑特征表示的链路预测方法。对不同的元路径根据异质和同质信息网络拓扑特征获得异质和同质数据,将逻辑回归模型作为链路预测模型,并综合拓扑特征进一步提高预测准确率。在异质的movielens电影数据集上进行实验,结果表明,该方法可有效提高异质信息网络演员合作关系的链路预测性能。

关键词: 异质信息网络, 同质信息网络, 分类算法, 链路预测, 元路径

Abstract: In heterogeneous information network,heterogeneous characteristics and complexities of the nodes and links increase the difficulty of link prediction.Aiming at this problem,this paper proposes a link prediction method by using synthetic topology characteristics.For different meta-paths,it uses the topology characteristics of heterogeneous and homogeneous information network to obtain heterogeneous and homogeneous data.It uses Logistic Regression(LR) model as a link prediction model,and integrates topology characteristics to further improve the prediction accuracy.Experimental results in real heterogeneous movielens film data sets show that the proposed method can improve the link prediction performance of actor cooperation relationship in heterogeneous information network.

Key words: heterogeneous information network, homogeneous information network, classification algorithm, link prediction, meta-path

中图分类号: