In many applications, association rules will only be interesting if they represent non-trivial correlations between all constituent items. Numerous techniques have been developed ...
Mining data streams of changing class distributions is important for real-time business decision support. The stream classifier must evolve to reflect the current class distributi...
Haixun Wang, Jian Yin, Jian Pei, Philip S. Yu, Jef...
In this paper, we propose a novel probabilistic approach to summarize frequent itemset patterns. Such techniques are useful for summarization, post-processing, and end-user interp...
This paper presents an LDA-style topic model that captures not only the low-dimensional structure of data, but also how the structure changes over time. Unlike other recent work t...
An organization makes a new release as new information become available, releases a tailored view for each data request, releases sensitive information and identifying information...
We describe a data mining system to detect frauds that are camouflaged to look like normal activities in domains with high number of known relationships. Examples include accounti...
Let R be a set of objects. An object o R is an outlier, if there exist less than k objects in R whose distances to o are at most r. The values of k, r, and the distance metric ar...
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...