TAILLANDIER, Patrick; TAILLANDIER, Franck

doi:10.1016/j.ejor.2011.10.004

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TAILLANDIER, Patrick
Cartographie et Géomatique [COGIT]
Identité et Différenciation de l’Espace, de l’Environnement et des Sociétés [IDEES]

TAILLANDIER, Franck

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European Journal of Operational Research. 2012-03-16, vol. 217, n° 3, p. 633-642

Elsevier

Résumé en anglais

The development of interactive map websites increases the need of efficient automatic cartographic generalisation. The generalisation process, which aims at decreasing the level of details of geographic data in order to produce a map at a given scale, is extremely complex. A classical method for automating the generalisation process consists in using a heuristic tree-search strategy. This type of strategy requires having high quality control knowledge (heuristics) to guide the search for the optimal solution. Unfortunately, this control knowledge is rarely perfect and its evaluation is often difficult. Yet, this evaluation can be very useful to manage knowledge and to determine when to revise it. The objective of our work is to offer an automatic method for evaluating the quality of control knowledge for cartographic generalisation based on a heuristic tree-search strategy. Our diagnosis method consists in analysing the system's execution logs, and in using a multi-criteria analysis method for evaluating the knowledge global quality. We present an industrial application as a case study using this method for building block generalisation and this experiment shows promising results.< Réduire

Mots clés en anglais

Multiple criteria analysis

Knowledge-based systems

Control knowledge quality diagnosis

Heuristic tree-search strategy

Cartographic generalisation

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Multi-criteria diagnosis of control knowledge for cartographic generalisation

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