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A scalable method for mining graph patterns stable under subsampling is proposed. The existing subsample stability and robustness measures are not antimonotonic according to definitions known so far. We study a broader notion of antimonotonicity for graph patterns, so that measures of subsample stability become antimonotonic. Then we propose gSOFIA for mining the most subsample-stable graph patterns...
Contrary to many application domains, recommending items within a museum is not only a question of preferences. Of course, the visitors expect suggestions that are likely to interest or please them. However, additional factors should be taken into account. Recent works use the visiting styles [1] or the shortest distance between items [2] to adapt the list of recommendations. But, as far as we know,...
With an increased interest in machine processable data, many datasets are now published in RDF (Resource Description Framework) format in Linked Data Cloud. These data are distributed over independent resources which need to be centralized and explored for domain specific applications. This paper proposes a new approach based on interactive data exploration paradigm using Pattern Structures, an extension...
The problem addressed in this paper is the merging of numerical information provided by several sources. Merging conflicting pieces of information into an interpretable and useful format is a tricky task even when an information fusion method is chosen. The use of formal concept analysis and pattern structures enables us to associate subsets of sources to combination results obtainable from consistent...
Functional classification involves grouping genes according to their molecular functions or the biological processes they participate in. This unsupervised classification task is essential for interpreting gene datasets produced by post-genomic experiments. As the functional annotation of genes is mostly based on the Gene Ontology (GO), many similarity measures using the GO have been described, but...
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