Neli Zlatareva

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This paper presents a methodology for testing general non-monotonic knowledge bases for logical and semantic inconsistencies. It extends the CTMS-based verification framework introduced in our previous work with an additional integrity test. This test aims to ensure that a logically consistent non-monotonic knowledge base is also free of semantic(More)
Ensuring the consistency and completeness of Semantic Web ontologies is practically impossible, because of their scale and highly dynamic nature. Many web applications, therefore, must deal with vague, incomplete and even inconsistent knowledge. Rules were shown to be very effective in processing such knowledge, and future web services are expected to(More)
Ontology alignment is regarded as one of the core tasks in many Web services. It is concerned with finding the correspondences between separate ontologies by identifying concepts with the same or similar semantics in order to resolve semantic heterogeneity between them. Existing ontology alignment techniques are tailored towards today's ontology languages,(More)
The inherent vagueness and ambiguity of non-monotonic reasoning makes it impossible to formulate detailed specifications to validate KBS performance by using traditional test-case-based approach. In this paper, we present a practical validation technique for non-monotonic KBSs, which utilizes automatically generated test cases instead. We show how such test(More)
To ensure that Expert System (ES) performance remains above the level of acceptance throughout the entire life cycle of the system, its knowledge base must periodically be updated and upgraded. In this paper, we review refinement activities taking place during ES development and exploits-tion, and outline a domain-independent refinement framework intended(More)
As a result of a large-scale invasion of expert systems (ES) in almost all areas of human life, a major problem related to their quality and reliability was identified. This paper presents a possible solution to this problem which consists of extending the function-ality of expert systems with a built-in quality assurance facility to allow the ES developer(More)