With the growth of the Internet and E-commerce, bipartite rating networks are ubiquitous. In such bipartite rating networks, there exist two types of entities: the users and the o...
Frequent behavioural pattern mining is a very important topic of knowledge discovery, intended to extract correlations between items recorded in large databases or Web acces logs....
Linear Support Vector Machines (SVMs) have become one of the most prominent machine learning techniques for highdimensional sparse data commonly encountered in applications like t...
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...
The goal of spatial co-location pattern mining is to find subsets of spatial features frequently located together in spatial proximity. Example co-location patterns include servi...