Weike Pan

Multi-behavior recommendation, unlike traditional single-behavior recommendation focusing solely on the target behavior (e.g., purchase), exploits multiple types of user-item interactions (e.g., view, favorite, add-to-cart, purchase) to mitigate data sparsity and learn more comprehensive user pre...

ID-based sequential recommendation (SR) methods learn user preferences based on the item-ID interaction sequences, which are often limited by the data sparsity problem. Large language model (LLM)-enhanced SR methods leverage LLM to improve the performance. Although prior works have made significa...