Discovery of association rules from large databases of item sets is an important data mining problem. Association rules are usually stored in relational databases for future use i...
Computing frequent itemsets is one of the most prominent problems in data mining. We study the following related problem, called FREQSAT, in depth: given some itemset-interval pai...
This survey paper categorises, compares, and summarises from almost all published technical and review articles in automated fraud detection within the last 10 years. It defines t...
Clifton Phua, Vincent C. S. Lee, Kate Smith-Miles,...
We study the mining of interesting patterns in the presence of numerical attributes. Instead of the usual discretization methods, we propose the use of rank based measures to scor...
Long-term search history contains rich information about a user's search preferences. In this paper, we study statistical language modeling based methods to mine contextual i...