Publications
Learning to Construct Knowledge Bases from the World Wide Web
Craven, M.; DiPasquo, D.; Freitag, D.; McCallum, A.; Mitchell, T.; Nigam, K. & Slattery, S.
Artificial Intelligence, 118(1-2) 69-113 (2000) [pdf]
Webwatcher: A tour guide for the World Wide Web
Joachims, T.; Freitag, D. & Mitchell, T.
, 'Proceedings of the International Joint Conference on
Artificial Intelligence (IJCAI)', Morgan Kaufmann, San Francisco, CA, 770-777 (1997)
The structure and function of complex networks
Newman, M. E. J.
(2003) [pdf]
Inspired by empirical studies of networked systems such as the Internet,
cial networks, and biological networks, researchers have in recent years
veloped a variety of techniques and models to help us understand or predict
e behavior of these systems. Here we review developments in this field,
cluding such concepts as the small-world effect, degree distributions,
ustering, network correlations, random graph models, models of network growth
d preferential attachment, and dynamical processes taking place on networks.