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Clustering of conceptual graphs with sparse data
pp. 156-169
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.
Publication details
Published in:
Wolff Karl Erich, Pfeiffer Heather D., Delugach Harry (2004) Conceptual structures at work: 12th international conference on conceptual structures. Dordrecht, Springer.
Pages: 156-169
DOI: 10.1007/978-3-540-27769-9_10
Full citation:
Ganascia Jean-Gabriel (2004) „Clustering of conceptual graphs with sparse data“, In: K. Wolff, H. D. Pfeiffer & H. Delugach (eds.), Conceptual structures at work, Dordrecht, Springer, 156–169.