Text mining with conceptual graphs
Manuel Montes-y-Gómez, Alexander F. Gelbukh, Aurelio López‐López, Ricardo A. Baeza-Yates · 2002
A method for conceptual clustering of a collection of texts represented with conceptual graphs is presented. It uses an incremental strategy to construct the cluster hierarchy and incorporates some characteristics attractive for text mining purposes. For instance, it considers the structural information of the graphs, uses domain knowledge to detect the clusters with generalized descriptions, and uses a user-defined similarity measure between the graphs.