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	HINE: Heterogeneous Information Network Embedding
	Chen, Yuxin ; Wang, Chenguang
	2017
关键词	Heterogeneous information network Network embedding Semantic embedding
英文摘要	Network embedding has shown its effectiveness in embedding homogeneous networks. Compared with homogeneous networks, heterogeneous information networks (HINs) contain semantic information from multi-typed entities and relations, and are shown to be a more effective model for real world data. The existing network embedding methods fail to explicitly capture the semantics in HINs. In this paper, we propose an HIN embedding model (HINE), which consists of local and global semantic embedding. Local semantic embedding aims to incorporate entity type information via embedding the local structures and types of the entities in a supervised way. Global semantic embedding leverages multihop relation types among entities to propagate the global semantics via a Markov Random Field (MRF) to impact the embedding vectors. By doing so, HINE is capable to capture both local and global semantic information in the embedding vectors. Experimental results; Natural Science Foundation of China [61572043]; National Key Research and Development Program [2016YFB1000704]; CPCI-S(ISTP); 180-195; 10177
语种	英语
出处	22nd International Conference on Database Systems for Advanced Applications (DASFAA)
DOI标识	10.1007/978-3-319-55753-3_12
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/480765]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Chen, Yuxin,Wang, Chenguang. HINE: Heterogeneous Information Network Embedding. 2017-01-01.

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