國民飲食與生活習慣之改變,以致罹患慢性病例逐漸攀升。有鑑於此,本論文針對醫療領域和飲食領域提出複合知識本體論(Complex Ontology, CO),分別依國際疾病標準碼(International Classification of Diseases - Clinical Modification, ICD-CM)描述醫療本體(Medical Ontology, MO)之疾病分類,以及依營養師建議之食物分類描述飲食本體(Diet Ontology, DO)。透過此複合知識本體讓本體中每個節點皆可得到交叉與繼承的關係,以建立飲食限制與最大門檻值之設限。最後,採用背包問題演算法,針對使用者的健康與飲食偏好推薦最佳飲食組合給予使用者。 在系統實作部份將以慢性疾病-高血壓進行案例解析,將高血壓之生理因子放置於醫療本體,藉以得知高血壓疾病之飲食重要影響因子為鈉,再透過食物本體得知每樣食物之鈉含量。當使用者選取偏好之食物後,即可立即藉由背包問題演算法推薦食物之組合。
With the change of diet habit and lifestyle in Taiwan, the quantity of chronic disease patients is becoming more and more. Therefore, we propose the Complex Ontology (CO) which includes Medical Ontology (MO) and Diet Ontology (DO) to build the diet limitations. For ontology description and building, we refer ICD-CM (International Classification of Diseases, Clinical Modification) and dietitian’s recommendation to define and classify the diseases into MO and the foods into DO, respectively. Finally, we use the Knapsack Problem Algorithm (KPA) to infer the optimum food collocation according to user’s physiology state, health, and diet preference. In this study, we implement the Intelligent Context-Aware Healthcare System (ICHS) based on CO for the chronic disease patients (e.g. hypertension). The ICHS can collect the user’s physiology state and diet preference through sensor devices to infer user’s diseases and retrieve the diet limitations (e.g. sodium) according to MO and DO. Afterward, the ICHS infers the optimum food collocation by KPA for diet recommendation.