Analysis and Semantic Mining in Heterogeneous Information Network - Rui Wang; Zhiqiang Zhang; Chuan Shi (Dianxin kexue, 2015)
Heterogeneous information network（HIN），which is composed of different types of objects and links，has gradually become a hot topic in social network analysis.As a unique characteristic of HIN，meta path contains rich semantic information.Heterogeneous information network with values on links are ubiquitous in real world.Therefore，the traditional meta path，which doesn’t consider weight on links，can not exactly capture semantics in many cases.Related concepts of HIN were introduced and a brief introduction of applications of HIN was given.Then subtle semantic information in HIN was explored by extending the traditional meta path to weighted meta path.Experiments on two real data sets demonstrate the applications of the weighted meta path in recommendation，relevance search.