Abstract
Configuration technologies are well established in different product domains such as financial services, cars, and railway interlocking stations. In many cases the underlying configuration knowledge bases are large and complex have a high change frequency. In the context of configuration knowledge base development and maintenance, different types of knowledge base anomalies emerge, for example, inconsistencies and redundancies. In this paper we provide an overview of techniques and algorithms which can help knowledge engineers and domain experts to tackle the challenges of anomaly detection and elimination. Furthermore, we show the integration of the presented approaches in the ICONE configuration knowledge base development and maintenance environment.
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Felfernig, A., Reinfrank, F., Ninaus, G. (2012). Resolving Anomalies in Configuration Knowledge Bases. In: Chen, L., Felfernig, A., Liu, J., Raś, Z.W. (eds) Foundations of Intelligent Systems. ISMIS 2012. Lecture Notes in Computer Science(), vol 7661. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34624-8_36
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DOI: https://doi.org/10.1007/978-3-642-34624-8_36
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