User-Centric Item Characteristics for Modeling Users and Improving Recommendations

Abstract

The PhD research presented in this paper discusses the idea of using user-centric item characteristics (UCIC) such as the eudaimonic/hedonic quality of multimedia items for achieving a better performance of the recommender systems. UCIC is the characteristics of the item that has its root in the way users perceive the item. Different users have different perceptions and therefore UCIC is a distribution of these perceptions of the item characteristic. For example, movies have a different value of UCIC concerning the induced emotion in users. Therefore, the quality of induced emotion is the characteristic of the item that its value is changed based on how the item is triggering different emotional reactions in users. One of our objectives is to predict the value of UCIC for the items. One possibility of describing UCIC can be by predicting mean and standard variation of perception of users of the specific item characteristic. Another objective is to use the variance in perception of the item characteristic in different users to personalize the recommendations based on the predicted score of the perceived item characteristic for different users. The thesis is composed of three original scientific contributions: (i) devise a method for labeling items with UCIC value and in particular the UCIC of hedonic/eudaimonic quality, (ii) devise models of user behavior based on the perception of item characteristic and in particular eudaimonic/hedonic perception, (iii) devise recommender systems with the incorporation of UCIC concepts for generating more accurate recommendations.