Sequence mining under multiple constraints
Nicolas Béchet, Peggy Cellier, Thierry Charnois, Bruno Crémilleux · 2015
In this paper, we address the problem of mining sequential patterns under multiple constraints. Unlike classical algorithms, our approach handles various types of constraints which are not only numeric but also symbolic and syntactic. These multiple constraints enable us to express a large scope of knowledge to focus on interesting patterns. We illustrate our approach with the detection of gene--rare disease relationships from biomedical texts for the documentation of rare diseases.