As the world moves towards greater automation, the need for intelligent algorithms to facilitate decision-making processes is becoming increasingly crucial. In this regard, contextual bandits have emerged as a powerful tool for addressing adaptive learning and decision-making challenges in various real-world applications. This blog post will delve into the theoretical underpinnings of contextual bandits, elucidating …
In recent years, sequential recommender systems have emerged as a popular approach for providing personalized recommendations to users. These systems take into account the order in which items are consumed by users, enabling them to identify long-term and short-term interests of users and predict their future preferences accurately. However, while sequential recommender systems have proven …
Introduction Recommender systems have revolutionized the way we discover new products, music, movies, and even potential romantic partners. They analyze users’ past interactions with items and provide personalized recommendations based on their preferences. However, traditional recommender systems face several challenges, such as sparsity, cold-start, and scalability. To overcome these limitations, researchers have been exploring the …
Transform Your Recommender System with Temporal Graph Neural Networks Read More »
Introduction The explosion of data in recent years has led to an ever-increasing need for effective recommender systems. These systems are designed to analyze user behavior and preferences and provide recommendations for products, services, or content that are likely to be of interest to them. One of the most promising approaches to building these systems …
Building Recommender Systems with Graph Generative Models Read More »
Introduction Recommender systems have become an integral part of our daily lives, whether it be for online shopping, music streaming, or social media recommendations. These systems use a combination of data mining, machine learning, and artificial intelligence to predict user preferences and make personalized recommendations. However, as the amount of data available to these systems …
Graph Neural Networks in Recommender Systems: Improving Accuracy and Personalization Read More »
Introduction In recent years, music streaming platforms such as Spotify and Apple Music have become increasingly popular. As a result, there is a growing need to analyze and predict the ratings of songs in order to improve the user experience and recommend the most relevant songs. In this post, we will discuss how to use …
