Cold-start recommendation — where little or no prior interaction data exists for a user or item — remains one of the most challenging problems in recommender systems. Large language models (LLMs) have shown promise in addressing this by leveraging rich semantic knowledge, but…

Diverse recommendations strongly correlate with increased sales diversity, perceived ease of use, and general user satisfaction with recommendation systems. However, many recommendation models focus only on maximizing recommendation accuracy. This can lead to a lack of diversity…

We survey the network properties and response to damage sustained of road networks of cities worldwide, using OpenStreetMap (OSM) data. We find that our primary damage response variable , which is the average shortest time needed to reach all nodes in a road network (which stand…

Forecasting reservoir water levels is essential in water supply management, impacting both operations and intervention strategies. This paper examines the short-term and long-term forecasting performance of several statistical and machine learning-based methods for predicting the…

One of the main problems in the study of human migration is predicting how many people will migrate from one place to another. An important model used for this problem is the radiation model for human migration, which models locations as attractors whose attractiveness is…