원문정보
초록
영어
In the past, eating outside was usually the purpose of eating. However, it has recently expanded into a restaurant culture market. In particular, a dessert culture is being established where people can talk and enjoy. Each consumer has a different tendency to buy chocolate such as health, taste, and atmosphere. Therefore, it is time to recommend chocolate according to consumers' tendency to eat out. In this paper, we propose a chocolate recommendation application based on the tendency to eat out using data on social networks. To collect keyword-based chocolate information, Textom is used as a text mining big data analysis solution.Text mining analysis and related topics are extracted and modeled. Because to shorten the time to recommend chocolate to users. In addition, research on the propensity of eating out is based on prior research. Finally, it implements hybrid app base.
목차
1. Introduction
2. Relevant Research
2.1 Food consumption propensity
2.2 empirical analysis
2.3 general characteristics of a sample
2.4 Reliability and Feasibility Verification
3. Research design
3.1 Research Model Diagram
3.2 Social network data collection
4. Recommended applications for chocolate based on the tendency of eating out using data on social networks
4.1 Chocolate Recommendation System Components
4.2 Chocolate Topic Map Model Results
4.3 syquins diagram
4.4 chocolate recommendation application
5. Conclusion
Reference