In practice, learning from data is often hampered by the limited training examples. In this paper, as the size of training data varies, we empirically investigate several probabil...
Heterogeneous information networks that contain multiple types of objects and links are ubiquitous in the real world, such as bibliographic networks, cyber-physical networks, and ...
Discovering patterns with highly significance is an important problem in data mining discipline. An episode is defined to be a partially ordered set of events for a consecutive an...
Semantic understanding of multimedia content is critical in enabling effective access to all forms of digital media data. By making large media repositories searchable, semantic ...
Classification is a core task in knowledge discovery and data mining, and there has been substantial research effort in developing sophisticated classification models. In a parall...
Ariel Fuxman, Anitha Kannan, Andrew B. Goldberg, R...