Diginetica

The 'Diginetica' dataset is a benchmark that contains user behavior sequences for session-based recommendation tasks, used to evaluate methods for predicting future user interests based on these anonymous interactions.

Papers using Diginetica (9)

Session-based Recommender Systems: User Interest as a Stochastic Process in the Latent Space2025Rethinking the Item Order in Session-based Recommendation with Graph Neural Networks2019 · 408 citesExploiting Cross-Session Information for Session-based Recommendation with Graph Neural Networks2021 · 155 citesExploiting Group-level Behavior Pattern forSession-based Recommendation2020SR-HetGNN:Session-based Recommendation with Heterogeneous Graph Neural Network2021STAR: A Session-Based Time-Aware Recommender System2022Optimizing Encoder-Only Transformers for Session-Based Recommendation Systems2024Multi-Graph Co-Training for Capturing User Intent in Session-based Recommendation2024SPGL: Enhancing Session-based Recommendation with Single Positive Graph Learning2024