1994 | OriginalPaper | Chapter
Combining a knowledge-based system and a clustering method for a construction of models in ill-structured domains
Authors : Karina Gibert, Ulises Cortés
Published in: Selecting Models from Data
Publisher: Springer New York
Included in: Professional Book Archive
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
Standard statistical methods usually ignore the additional information that an expert has about the domain structure. Direct treatment of symbolic information is not a very common characteristic of statistical systems. KLASS is a statistical clustering system that provides the possibility of using either quantitative and qualitative variables in the domain description. The user may also declare part of its knowledge about the domain structure. The system is especially useful when dealing with ill-structured domains (i.e. a domain where the consensus among the experts is weak as mental diseases, sea sponges, books, painters…). That is why it is also useful from the artificial intelligence point of view. The output is a partition of the target domain. Conceptual and extensional descriptions of the classes can also be achieved.