One fundamental challenge for mining recurring subgraphs from semi-structured data sets is the overwhelming abundance of such patterns. In large graph databases, the total number ...
There is a huge wealth of sequence data available, for example, customer purchase histories, program execution traces, DNA, and protein sequences. Analyzing this wealth of data to ...
In this paper we introduce a new type of pattern – a flipping correlation pattern. The flipping patterns are obtained from contrasting the correlations between items at diffe...
Marina Barsky, Sangkyum Kim, Tim Weninger, Jiawei ...
Temporal Text Mining (TTM) is concerned with discovering temporal patterns in text information collected over time. Since most text information bears some time stamps, TTM has man...
Learning to predict rare events from sequences of events with categorical features is an important, real-world, problem that existing statistical and machine learning methods are ...