Integrated quality assessment of services in an adaptive expert system with a rule-based knowledge base

Abstract

Abstract One of the basic tasks of companies providing services is care for their quality. The quality of services is not only demonstrated by the requirements of service users, but also by applicable industry standards, specifications, economic and financial conditions. The process of quality assessment require knowledge about the quality measures (expressed in numerical form or as a text description). Acquiring that knowledge is the most significant step to quality assessment. The article presents architecture of expert systems used to explain and asses that knowledge with a rule-based knowledge base (built with integration of data text analysis modulatory methods and rule-based exploration of numerical data). Such databases, with additional ontology integration methods, are more adaptable to new quality measures and data sources. Expert systems form quality standards and a reference to the quality assessment forecast.