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Representing knowledge patterns in a conceptual database design aid : a dual-base knowledge model

By Tsiar-Yuan Chang


The current status of the Knowledge-Based Database Design Systems (KBDDSs)\ud is reviewed. It is shown that they do not resolve the problems of the identification\ud of the relevant objects (relations) and the interpretation of the identified objects\ud from the semantic-rich reality.\ud Consequently, a theoretical architecture is developed to alleviate these problems\ud by reusing the finished conceptual data schemata. By taking account of the\ud essence of the reality and the problem-solving behaviour of experts, a new\ud knowledge model called the Dual-Base Knowledge Model (DBKM), which\ud involves two syngeristic knowledge structures, the concept and case bases, is\ud constructed by the theories of conceptual knowledge in the psychological realm\ud and the notions of relation and function from set theory. The aim is to provide\ud rational and valid grounds for the support and interplay of these two bases in order\ud to reuse the relevant old cases and facilitate the acquisition of new cases. Thus,\ud the process model, which involves two process mechanisms, the case retrieval and\ud knowledge accumulation mechanisms, is analysed according to the theory of the\ud proposed DBKM. In this way, the feasibility of reusing the relevant schemata or\ud part of them can be established in the DBKM architecture.\ud The functionality of the DBKM architecture is tested by a simulated example to\ud show how the relevant cases are recalled in the knowledge pool and the new\ud knowledge is stored in the knowledge repository. The distinctions between the\ud DBKM architecture and the frameworks of current KBDDSs and Case-Based\ud Reasoning (CBR) systems (from the knowledge-based system view), and between\ud the DBKM and those knowledge models in current KBDDSs and rule-based data\ud modelling approaches (from the knowledge-modelling view) are investigated to\ud contrast the current levels of progress of the conceptual data modelling.\ud This research establishes the feasibility of the DBKM architecture, although it\ud demonstrates the need to accommodate the dynamic and functional aspects of the\ud Universe of Discourse (UoD). The main contributions of the DBKM are (1) to\ud provide a valid basis for complementing the environments supported by the\ud current KBDDSs and a rational basis for creating the symbiosis of humans and\ud computer; and (2) to moderate the beliefs underlying the fact-based school and\ud provide a hermeneutic environment, so that the confusion of the current\ud conceptualising work can be alleviated and the difficulty of the conceptualising\ud task can be eased to some degree

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