A binary matrix is fully nested if its columns form a chain of subsets; that is, any two columns are ordered by the subset relation, where we view each column as a subset of the r...
Identifying the extremal (minimal and maximal) sets from a collection of sets is an important subproblem in the areas of data-mining and satisfiability checking. For example, ext...
The biclustering, co-clustering, or subspace clustering problem involves simultaneously grouping the rows and columns of a data matrix to uncover biclusters or sub-matrices of the...
Outlier scores provided by different outlier models differ widely in their meaning, range, and contrast between different outlier models and, hence, are not easily comparable o...
Motivated by sensor networks, mobility data, biology and life sciences, the area of mining uncertain data has recently received a great deal of attention. While various papers hav...
Francesco Bonchi, Matthijs van Leeuwen, Antti Ukko...
Latent semantic analysis (LSA), as one of the most popular unsupervised dimension reduction tools, has a wide range of applications in text mining and information retrieval. The k...
Xi Chen, Yanjun Qi, Bing Bai, Qihang Lin, Jaime G....
Popular data mining methods support knowledge discovery from patterns that hold in binary relations. We study the generalization of association rule mining within arbitrary n-ary ...
Extracting semantic relations between entities is an important step towards automatic text understanding. In this paper, we propose a novel Semi-supervised Convolution Graph Kerne...
A nonparametric Bayesian approach to co-clustering ensembles is presented. Similar to clustering ensembles, coclustering ensembles combine various base co-clustering results to ob...
Pu Wang, Kathryn B. Laskey, Carlotta Domeniconi, M...