This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
We introduce the notion of iceberg concept lattices and show their use in knowledge discovery in databases. Iceberg lattices are a conceptual clustering method, which is well suit...
Gerd Stumme, Rafik Taouil, Yves Bastide, Nicolas P...
Subspace learning techniques are widespread in pattern recognition research. They include Principal Component Analysis (PCA), Locality Preserving Projection (LPP), etc. These tech...
Digital Libraries will hold huge amounts of text and other forms of information. For the collections to be maximally useful, they must be highly organized with useful indexes and ...
Robert P. Futrelle, Xiaolan Zhang 0002, Yumiko Sek...
We present a graph-theoretic approach to discover storylines from search results. Storylines are windows that offer glimpses into interesting themes latent among the top search re...