Relation Strength-Aware Clustering of Heterogeneous Information Networks With Incomplete Attributes
With the rapid emergence of online social media, online shopping sites and cyber-physical systems, it has become possible to model many forms of interconnected networks as heterogeneous information networks in which objects (i.e., nodes) are of different types, and links among objects correspond to different relations, denoting different interaction semantics. An object is usually associated with some attributes. With the rapid development of online social media, online shopping sites and cyber-physical systems, heterogeneous information networks have become increasingly popular and content-rich over time. In many cases, such networks contain multiple types of objects and links, as well as different kinds of attributes. The clustering of these objects can provide useful insights in many applications.