Recommendation method of smart TV programs reflecting content consumption concentration calculation

Abstract

The proliferation of smart TVs and the surge of broadcasting contents due to the effects of Internet broadcasting and the creation of comprehensive programming channels have provided an environment in which various programs can be selected and consumed by TV viewers today. However, it is very time-consuming for users to select the programmes that people want by identifying the contents of a large number of programmes. Therefore, it is necessary to study the recommendation of TV programmes with high user satisfaction based on the user's viewing history. However, the research to date does not consider how focused the programme was when generating a list of programmes viewed by the user. As a result, we recommend TV programmes with relatively low satisfaction by recommending TV programme without distinction between the TV programme and the TV programme. In this study, we propose a method to calculate the concentration of content consumption based on user's TV programme consumption pattern and to recommend smart TV programme based on it. In order to verify the proposed method, we compared the satisfaction with the existing method based on the TV viewing records of the top 100 who had many TV watching records.