Multimedia content recommendation in social networks using mood tags and synonyms

Abstract

The preferences of Web information purchasers are changing. Cost-effectiveness (i.e., an emphasis on performance with respect to price) is becoming less regarded than cost-satisfaction, which emphasizes the purchaser’s psychological satisfaction. A method to improve a user’s cost-satisfaction in recommending multimedia content is to use the mood-inherent in multimedia items. An example of applications using this method is SNS (Social Network Services) based on mood folksonomy. However, such applications encounter problems due to synonyms. This paper suggests a cost-satisfactory method of multimedia content recommendation to solve the problem of synonyms. It utilizes arousal and valence (AV), which express the mood of multimedia content, as its internal tag. A method that defines the relationship between the AV values of multimedia content and the AV values of mood tags is suggested by considering synonyms and the correlations between them. Furthermore, a multimedia content-recommendation method based on the relationship is suggested and tested. The analysis shows that the AV values of multimedia content with a mood tag and its synonyms reside in the area of the mood tag in the Thayer model. The performance of this method exceeds that of a keyword-based recommendation method.