• 한국식품영양과학회지
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• 제23권5호
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• pp.774-783
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• 1994

New food item numbers for each food included in Food Composition Table in Korea (4th ed) and other Food Composition Table. New Food item numbers classified to base 5-basic food groups and its classification was as follows. 1 As for the 1569 food items , they were classified as 20 food sub-groups(82 food sorts) for 5-basic food groups. 2. As for the 82 food sorts, they were individually classified with raw prepared , fat sugar content and arranged in order, ㄱ , ㄴ and ㄷ and made the item number. 3. The data set of nutritive value of food with new item numbers was accessed on computer files. 4. The Food & Description Table was drafted as 1572 food items were arranged in order, ㄱ, ㄴand ㄷ. 5. The Food Table arranged in the order or each nutrient content (energy, carbohydrate, protein , etc....) was drafted. Clipper program for computing nutritive values and tabulation of nutrients of daily diet were coded by applying new food item numbers. It is expected that should utilized as a basic data of computer program for calculating the nutritive value of diet, evaluating the nutrition and counseling the nutrition.

• Journal of Nutrition and Health
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• 제20권6호
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• pp.442-455
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• 1987

The purpose of the study were to assist foodservice managers in complex decision making by utilizing computerized cost accounting system and to relieve managers from repetitive and routine tasks so that more adequate patient care and consultation can be provided. The scope of the computer-assisted cost accounting system consists of budget, menu planning, purchasing, inventory, cost control and financial reporting. The content of the computerized system are summarized as follows ; 1) For budgeting monthly income was estimated by calculating unit cost of each meal and forecasting serving numbers. The actual serving numbers for patients and employees were totaled everyday, and utilized as the basic data base for estimating income and planning menu. The monthly lists of meal sensus were generated. 2) for menu planning concersion factors were computed based on the standarized recipe for 50 servings. Daily menus for patients and employees which include total amounts of each ingredient and cost analyzed information were generated. 3) Daily and monthly purchasing report for each food item classified by patient and employee meals were generated. 4) Inventory transactions such as recipts and issues were totalized daily for each stocked item, and monthly inventory reports were generated. 5) Cost analysis reports for each menu item were generated into two ways based on the budget coat as well as the purchasing cost. 6) Editing new recipes and updating food costs change to the data base were carried out. 7) Financial reports were generated monthly, first-half and second-half of the year, and yearly basis.

• 한국컴퓨터정보학회논문지
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• 제25권6호
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• pp.81-89
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• 2020

우리가 SNS상에서 흔하게 접하는 온라인 리뷰에는, 소비자들의 선호도에 영향을 미치는 다양한 평가정보가 복합적으로 포함되어 있지만 이를 매우 간단한 형태의 수치(또는 평점)로 제공하는 것이 일반적이다. 이러한 리뷰에서, 소비자가 원하는 구체적인 정보를 얻고, 이를 구매를 위한 판단에 활용하기란 쉽지 않다. 따라서 본 연구에서는 한국어로 작성된 음식점 리뷰를 대상으로, 감성분석을 수행하여 평가항목별로 세분화된 평점을 제공 가능한 예측 방법론을 제안한다. 이를 위해, 음식점의 주요 평가항목으로 '음식', '가격', '서비스', '분위기'를 선정하고, 평가항목별 맞춤형 감성사전을 새롭게 구축한다. 또한 평가항목별 리뷰 문장을 분류하고 감성분석을 통해 세분화된 평점을 예측하여 소비자가 의사결정에 활용 가능한 추가적인 정보를 제공한다. 마지막으로, MAE와 RMSE를 평가지표로 사용하여 기존의 연구보다 제안기법의 평점 예측 정확도가 향상되었음을 보이며, 제안 방법론의 활용 사례도 제시한다.