餐點研發配料選材推薦方法與系統

The Ingredients Recommended Method and System for Meal Research and Development

食物是和大家的生活是習習相關，對於新式餐點的推出與嘗鮮更深受許多人的喜愛。 然而研發食材者通常要花費許多時間與食材成本來測試各種食材、配料與調味料的組合，本研究針對研發設計一餐點研發配料選材推薦方法之系統，其包括有：1）知名餐點配料種類暨份量比率統計分析系統：2）知名餐點調味料種類暨份量比率統計分析系統：3）餐點研發時配料種類暨配料比率推薦系統：4）餐點研發時調味料種類暨配料比率推薦系統：5）知名餐點配料使用之關聯規則探勘系統：6）知名餐點調味料使用之關聯規則探勘系統：7）跨餐點類別配料使用之關聯規則探勘系統，在問卷分析中的平均數排名在 4.15 以上（平均數排名的前四名)）分別為：「衛生安全」、「新鮮程度」、「口感」及「美味程度」，這四個變項皆都為「美味等級構面」，未來料理者建議如果有要研發餐點時可以參考這四個方面去研究。在實驗分析方面，國外資料庫有分析非洲、東亞、南亞和北美這四個，其中比較特別是東亞使用的食材會有醬油這個調味料。在關聯規則方面，整個探勘結果出現的次數前三名分別為：鹽、糖及水，這三個食材是非常重要。總之，本研究提供了餐 點研發者在面對新餐點做研發決策時，針對過去餐點進行資料分析與探勘，希望可以讓使用者在研發餐點時達事半功倍之效果。

Food is highly related to everyone's life. It is many people's favorite activity to taste the new launch of the meals. However, the R & D ingredients usually spend a lot of time and cost to test a variety of materials, ingredients, seasonings and combination. In this study, we developed one system embedded with a new meal ingredients recommended method. There are seven subsystems include: 1) the well-known meals' ingredients statistical analysis system; 2) the well-known meals'seasonings statistical analysis system; 3) the meal's ingredients type and ratio recommendation system; 4) the meal's seasonings type and ratio recommendation system 5) famous meal's ingredients data mining system with association rule; 6) famous meal's seasonings data mining system with association rule; 7) cross-meals category of ingredients data mining system with association rule. Through this system, it can consider multiple conditions such as material, price, ingredients and so on. It can also proceed with the data mining, analysis and recommendation for ingredient and seasoning.