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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© 2004 Springer-Verlag Berlin Heidelberg
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Ganascia, JG., Velcin, J. (2004). Clustering of Conceptual Graphs with Sparse Data. In: Wolff, K.E., Pfeiffer, H.D., Delugach, H.S. (eds) Conceptual Structures at Work. ICCS 2004. Lecture Notes in Computer Science(), vol 3127. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27769-9_10
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DOI: https://doi.org/10.1007/978-3-540-27769-9_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22392-4
Online ISBN: 978-3-540-27769-9
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