Authors:
Cyril de Runz
and
Eric Desjardin
Affiliation:
University of Reims Champagne-Ardenne, France
Keyword(s):
Fuzzy logic, Data mining, Imprecise temporal data, Fuzzy temporal relation, Archaeology, GIS.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Complex Fuzzy Systems
;
Computational Intelligence
;
Fuzzy Information Retrieval and Data Mining
;
Fuzzy Systems
;
Mathematical Foundations: Fuzzy Set Theory and Fuzzy Logic
;
Soft Computing
Abstract:
In this paper, we propose a new temporal data mining method considering a set of arch ae ological objects which are temporally represented with fuzzy numbers. Our method uses an index which quantifies the anteriority between two fuzzy numbers for the construction of a weighted oriented graph. The vertices of the graph correspond to the temporal objects. Using this anteriority graph, we estimate the potential of anteriority, of posteriority and the relative temporal position of each object. We focus on excavation data from the ancient Reims stored in a Geographical Information System (GIS). We visualize the discovered temporal positions of objects and weighted relations between them in a layer of the GIS.