Elevating Customer Value of media recommendations through Enhanced User Satisfaction and Development

Media recommender systems often fall short by prioritizing behavioral data over user perception and experience, resulting in a disconnect between user preferences and actual consumption. The intricacy of multi-dimensional user preferences poses a challenge, compounded by an intention-behavior gap in high-quality media consumption. Unintentional content consumption can be exacerbated by recommendations geared towards engagement or revenue goals, potentially leading to misguided outcomes. Consequently, there is a critical need to refine recommender system designs from a user-centric perspective, accounting for nuanced preferences and intrinsic needs.

This project takes a user-centric approach, delving into the role of media recommender systems in aligning user needs, preferences, and consumption. The overarching aim is to cultivate the generation of healthier, more beneficial recommendations, ultimately enriching user satisfaction and overall development.