New Trends in Artificial Intelligence for Recommender Systems and Collaborative Filtering.

In this Special Issue, we aim to widen the boundary of knowledge in CF-based RSs with new proposals incorporating cutting edge trends in artificial intelligence. There, the authors propose to apply RSs to suggest code repositories to software developers on the GitHub platform. Thus, the authors propose the KANR model, which is composed of three stages: an attention aggregation network to gather user features, a knowledge graph embedding to push these features into a latent space, and a final fusion component to provide the final predictions. In recent times, recommender systems (RSs) have been attracting a lot of attention from the research community because of their groundbreaking applications. [Extracted from the article]