| Summary: | 碩士 === 國立彰化師範大學 === 資訊管理學系 === 106 === In recent years, with the popularization of the Internet, various types of information are quickly disseminated on the Internet, users can easily find related products or services when searching, and excessive data volume may lead to tedious query results. Therefore, if Using recommended technologies to help users will be a good way to solve these problems. It is easy to understand that the recommendation mechanism can substantially improve consumer decision-making. However, how the design of the recommender mechanism affects the measurement of decisions or other results is seriously insufficient. Therefore, this study decided to use the “dual-coding theory” argument to examine the effectiveness of the recommender system.
This study constructs two recommender systems, one is a traditional recommender system, and the other is a recommender system based on the dual-coding theory. The experiment method is used to allow users to use the two systems separately to measure the two. Differences in various assessment indicators.
The experimental results show that the recommender system designed on the basis of the dual-coding theory is better than the traditional recommender system on all aspects of the facet. On the analysis of the main effect path, in addition to the perceive convenience on satisfaction, the rest of the path is significant.
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