A Study on Korea Food Recommendation Service Using Big Data Analysis
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초록
Recently, the proportion of restaurants and processed foods are increasing as various environmental changes and the number of families and double income continues to increase. As a result, changes in consumption patterns are diversifying, and obesity, diabetes, and characteristic are also increasing due to increased intake of health-hazardous nutrients such as sugars, sodium, and trans fat. Big data analysis is a process to find hidden patterns and unknown information from large amounts of data, focusing on providing predictive information rather than information on the current situation. Since it can accurately grasp customer trends, it is widely used to predict customer needs through various analyses. In particular, big data analysis on food products is considered to be very meaningful in that it can predict patterns and analysis of consumption behavior. In addition, it can be predicted that meaningful implications will be found in relation to the various views of customers in their daily lives that were not presented in previous studies conducted. Accordingly, this research aims to confirm consumers' perception of food by collecting and analyzing structured data related to food products between it is checked the keywords of Korean food products analyzed through big data and it is examined the characteristics of the connectivity between keywords related to Korean food products. Finally, we are intended to understand consumers' perceptions and desires for the analysis results of Korean food products.
Abstract
Recently, the proportion of restaurants and processed foods are increasing as various environmental changes and the number of families and double income continues to increase. As a result, changes in consumption patterns are diversifying, and obesity, diabetes, and characteristic are also increasing due to increased intake of health-hazardous nutrients such as sugars, sodium, and trans fat. Big data analysis is a process to find hidden patterns and unknown information from large amounts of data, focusing on providing predictive information rather than information on the current situation. Since it can accurately grasp customer trends, it is widely used to predict customer needs through various analyses. In particular, big data analysis on food products is considered to be very meaningful in that it can predict patterns and analysis of consumption behavior. In addition, it can be predicted that meaningful implications will be found in relation to the various views of customers in their daily lives that were not presented in previous studies conducted. Accordingly, this research aims to confirm consumers' perception of food by collecting and analyzing structured data related to food products between it is checked the keywords of Korean food products analyzed through big data and it is examined the characteristics of the connectivity between keywords related to Korean food products. Finally, we are intended to understand consumers' perceptions and desires for the analysis results of Korean food products.
참고문헌 (15)
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