Mining heterogeneous information networks

Abstract

Real world physical and abstract data objects are interconnected, forming gigantic, interconnected networks. By structuring these data objects into multiple types, such networks become semi-structured heterogeneous information networks. Most real world applications that handle big data, including interconnected social media and social networks, scientific, engineering, or medical information systems, online e-commerce systems, and most database systems, can be structured into heterogeneous information networks. For example, in a medical care network, objects of multiple types, such as patients, doctors, diseases, medication, and links such as visits, diagnosis, and treatments are intertwined together, providing rich information and forming heterogeneous information networks. Effective analysis of large-scale heterogeneous information networks poses an interesting but critical challenge.