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KNOWLEDGE-BASED SOFTWARE ENGINEERING phần 9

Không đóng trình duyệt đến khi xuất hiện nút TẢI XUỐNG Tải xuống

không dính nhau, và quyết định nếu trường hợp là cần thiết cho hệ thống hay không. Tất nhiên, các chuyên gia thần kinh học trước hết phải quyết định nếu chẩn đoán là chính xác. Việc đánh giá các tính chất vụ án là các bộ lọc bổ sung, cải thiện độ chính xác của hệ thống | M. Ivanovic et al. Role of Case-based Reasoning in Neurology Decision Support 261 incoherence and makes decision if the case is needed for the system or not. Of course the neurology expert must firstly decide if the diagnosis is correct. The evaluation of the case properties is the just additional filter which improves accuracy of the system and reduces the case base growth without losing of coưectness. In this phase of realisation the problem of forgetting is not realised. We will observe the growth of case base and if the growth will turn to be significant we will develop some forgetting algorithms based on deleting not recently used or least used cases. Pan of case retrieval ncl Information entities nodes Case nodes Acceptance arcs Rclcx ance arcs Fig. 3. Example of CRN in the neurology domain. As mentioned before cases are organized in the Case Retrieval Net. This net has nodes for each case and nodes for each value of every feature - these values are called information entities. There exists an acceptance arc between every two corresponding information entities - information entities of the same feature. Also there exists a relevance arc from information entity to the case if that information entity is relevant for that case. All the values in the net are weighted with appropriate values. In Fig. 3 a part of case retrieval net from this domain is given. In this figure only 3 features Spastically - 1.4 Bladder dysfunction - 1.8 Magnetic resonance imaging - IV 262 M. Ivanovic et al. Role of Case-based Reasoning in Neurology Decision Support with 3 values for each attribute and for different cases which makes 9 information entities are presented. Acceptance arcs are connecting only information entities nodes of the same feature which means that local acceptance function is defined only between information entities of the same feature. Furthermore only 3 cases Case 3 Case 4 Case 5 from this domain are presented in the figure. Relevance arcs represent the influence