- 學位論文
以本體為基準結合背包演算法之慢性病患飲食推薦
The Recommendation of Diet for Chronic Diseases Based on Knapsack Problem and Domain Ontology
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摘要
現今社會上有許多人罹患慢性病三高，但大多數的患者會先依據搜尋引擎找尋相關的飲食資訊，進而尋求營養專家的意見來做為自己飲食的規劃。但網路上之飲食資訊大多數是基於文字敘述，因此使用者必須尋找更多的飲食資訊結合，且網路上之資訊不是基於正式標準所定義的資訊的，因此在於知識的結構上較無規劃，由於上述兩點，對於使用者取得適當飲食資訊來說是比較不友善的。因此，本研究希望透過本體論的觀點，來建構一個具有專家知識之慢性病三高飲食推薦系統進而給予使用者更為完善且更為精確的飲食資訊。 本研究中使用Protege來輔助建立本體(ontology)結構知識庫。並使用模糊邏輯(fuzzy logic)做為系統之前導推論，依患者之身體資訊推論出適合使用者每日所需之總熱量值，並使用JENA做為我們的推論器建立我們的知識規則。最後整合類背包演算法將fuzzy logic與JENA推論之結果組合出適合使用者之三餐組合，實做出一個慢性病三高飲食推薦系統。並經由營養專家評估與驗證，本實驗之系統能提供營養專家推薦符合於人們現實生活的飲食結果。
並列摘要
Nowadays many people suffer from three high chronic diseases: just like diabetes, hypertension and high cholesterol, but people use search engine to find information related to diet and nutrition experts to give advice for diet recommendations. However, the dietary information on the network is mostly text-based narrative, so users must find more information about the diet combination. The diet information on the network is not based on ontology, so the knowledge is less friendly. The aims of this study are through the ontological of viewers to construct our diet recommendation system with the three high chronic diseases of expert’s knowledge. And we will give users more complete and more accurate information. In this study, we used Protege to establish our ontology and used OWL DL to construct the structure of knowledge. The system uses fuzzy logic as a guide prior to inference. According to the patient''s health information, the system infers daily calories requirement, and then use JENA inference device and use JENA rule format to build our knowledge of the rules. Finally, the Knapsack-like algorithm will combine the results. The reasoning results will recommender suitable foods for users. The system was evaluated by nutritionist to proof that the system is useful for three high chronic diseases.
參考文獻
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