ITM-Rec: An Open Data Set for Educational Recommender Systems
원문 초록
With the development of recommender systems (RS), several promising systems have emerged, such as context-aware RS, multi-criteria RS, and group RS. However, the education domain may not benefit from these developments due to missing information, such as contexts and multiple criteria, in educational data sets. In this paper, we announce and release an open data set for educational recommender systems. This data set includes not only traditional rating entries, but also enriched information, e.g., contexts, user preferences in multiple criteria, group compositions and preferences, etc. It provides a testbed and enables more opportunities to develop and examine various educational recommender systems.
함께 살펴볼 논문
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A Reproducibility Study of Product-side Fairness in Bundle Recommendation
NLGCL: Naturally Existing Neighbor Layers Graph Contrastive Learning for Recommendation
Boosting Parameter Efficiency in LLM-Based Recommendation through Sophisticated Pruning
Kamae: Bridging Spark and Keras for Seamless ML Preprocessing
FindRec: Stein-Guided Entropic Flow for Multi-Modal Sequential Recommendation
Thought-Augmented Planning for LLM-Powered Interactive Recommender Agent
토론
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