BBAuthors: Fang, Yuan; Advisor: -; Participants: Lin, Wenqing; W. Zheng, Vincent; Wu, Min; Shi, Jiaqi; Chang, Kevin Chen-Chuan; Li, Xiao-Li (2019)
Data in the form of graphs are prevalent, ranging from biological and social networks to citation graphs and the Web. In particular, most real-world graphs are heterogeneous, containing objects of multiple types, which present new opportunities for many problems on graphs. Consider a typical proximity search problem on graphs, which boils down to measuring the proximity between two given nodes. Most earlier studies on homogeneous or bipartite graphs only measure a generic form of proximity, without accounting for different “semantic classes”—for instance, on a social network two users can be close for different reasons, such as being classmates or family members, which represent two d... 
