A Museum Recommendation System based on Lifestyles

The existing recommendation system has been widely applied on electronic business field. In recent years, such system has been gradually stepped into the digital teaching field, the advantage of which is to know the preference and interest etc., factors of the learner so as to provide the learner with suitable learning contents. Due to the increasing number of new users and new displaying content, the recommendation system tends to confront with a situation that is incapable and invalid recommendation called "cold start" problem. In order to solve such problem, we introduce from the viewpoint of sociology to incorporate the lifestyle of the users into the museum recommendation system. This will enable the users inside the museum with a personalized learning service. The character of this system is to take the lifestyle of the users into consideration instead of the system act, further, to analyze the characteristics and to study the favorite displaying content of different clusters through questionnaire survey to take the lifestyle and cluster preference contents as the principle of recommendation items.