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Clustering of Conceptual Graphs with Sparse Data

Abstract : This paper gives a theoretical framework for clustering a set of conceptual graphs characterized by sparse descriptions. The formed clusters are named in an intelligible manner through the concept of stereotype, based on the notion of default generalization. The cognitive model we propose relies on sets of stereotypes and makes it possible to save data in a structured memory.
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Submitted on : Wednesday, May 10, 2017 - 3:49:41 PM
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Jean-Gabriel Ganascia, Julien Velcin. Clustering of Conceptual Graphs with Sparse Data. 12th International Conference on Conceptual Structures (ICCS), Jul 2004, Huntsville, United States. pp.156-169, ⟨10.1007/978-3-540-27769-9_10⟩. ⟨hal-01520556⟩



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