This study aimed to help people select an appropriate plate to enhance the quality of their dining experiences. Meals are not only a means of nutritional intake but also one of the “experiential contents” that enrich our daily lives. The attractiveness of a meal as an experience derives not only from the taste of the food, but also from its appearance, which includes the novelty of the ingredients and cooking methods, as well as presentation methods such as serving and coloring. The appearance of a dish is significantly influenced by its appearance and the plates on which it is served. Focusing on the point that “the plates enhance the attractiveness of the meal,” we attempted to develop plate recommendation methods to improve the quality of the dining experience. The selection of serving plates should consider the compatibility of the plates and the consistency of the plate with the other plates served together. Although qualitative criteria exist for these factors, no unique correct solution exists, which renders plate selection difficult. Enabling computers to understand and process these criteria will provide support for plate selection in line with human cognition. We assumed that two elements were necessary to support plate selection to improve the quality of the dining experience (QoD): “understanding the characteristics of each meal and plate, as well as the appropriate combination of both” and “reflecting user preferences.“ Thus, this study proposes the “meals—plates cycle” as a framework that satisfies the aforementioned two elements. This paper presents the design guidelines for the framework, data construction based on the guidelines, and the development of elemental technologies.