Temporal analysis of semantic graphs using ASALSAN ∗

http://csmr.ca.sandia.gov/~tgkolda/pubs/bibtgkfiles/ICDM07.pdf

ASALSAN is a new algorithm for computing three-way
DEDICOM, which is a linear algebra model for analyzing
intrinsically asymmetric relationships, such as trade among
nations or the exchange of emails among individuals, that
incorporates a third mode of the data, such as time. ASALSAN is unique because it enables computing the three-way
DEDICOM model on large, sparse data. A nonnegative version of ASALSAN is described as well. When we apply these
techniques to adjacency arrays arising from directed graphs
with edges labeled by time, we obtain a smaller graph on latent semantic dimensions and gain additional information
about their changing relationships over time. We demonstrate these techniques on international trade data and the
Enron email corpus to uncover latent components and their
transient behavior. The mixture of roles assigned to individuals by ASALSAN showed strong correspondence with
known job classifications and revealed the patterns of communication between these roles. Changes in the communication pattern over time, e.g., between top executives and
the legal department, were also apparent in the solutions.