In today’s rapidly evolving landscape, integrating automated systems into various aspects of daily tasks is a primary objective for both industry and academia. …
Graph Neural Networks (GNNs) have proven highly effective in graph-related tasks, including Traffic Modeling, Learning Physical Simulations, Protein Modeling, and Large-scale Recommender Systems. …
In this lab, we provide a hands-on experience to help users develop and evaluate novel Graph Counterfactual Explanation (GCE) methods using a simple and modular framework, GRETEL. …
Graph Neural Networks (GNNs) have proven highly effective in graph-related tasks, including Traffic Modeling, Learning Physical Simulations, Protein Modeling, and Large-scale Recommender Systems. …
Creating efficient and effective search and recommendation algorithms has been the main objective of industry practitioners …
This demo discusses the challenges of interpreting Graph Neural Networks (GNNs) in social networks and introduces Graph Counterfactual Explanation (GCE) methods as a solution …
Creating search and recommendation algorithms that are efficient and effective has been the main objective for the …
Both search and recommendation algorithms provide a user with a ranking that aims to match their needs and interests. …
Challenges and Solutions to the Student Dropout Prediction Problem in Online Courses a tutorial by Dr. B. Prenkaj, Prof. G. Stilo, and Dr. L. Madeddu, …
Search and recommendation are getting closer and closer as research areas. Though they require fundamentally …
Social media platforms have become powerful tools to collect the preferences of the users and get to know them more. Indeed, in order to build profiles about what they like or …
The data collected in social media platforms has become an important source of information, usually exploited by a social recommender system to generate suggestions …
Modern society is overwhelmed and characterized by exhausting social interactions at all levels. …
Recommender systems are widely used in different applications to support users in exploring possibly interesting items. To go beyond the use of preferences expressed in form of ratings, …
Social media platforms have become powerful tools to collect the preferences of the users and get to know them more. Indeed, in order to build profiles about what they like or dislike, a system does …
Recommender systems are widely used in different applications to support users in exploring possibly interesting items. To go beyond the use of preferences expressed in form of ratings, …