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A survey of collaborative filtering techniques
Multi-behavior recommendation datasets -
Modeling task relationships in multi-task learning with multi-gate mixture-of...
Multi-behavior recommendation datasets -
Recent Advances in Heterogeneous Relation Learning for Recommendation
Multi-behavior recommendation datasets -
Leveraging meta-path based context for top-n recommendation with a neural co-...
Multi-behavior recommendation datasets -
Compressed Interaction Graph based Framework for Multi-behavior Recommendation
Multi-behavior recommendation datasets -
MovieLens-100K and MovieLens-1M
MovieLens-100K and MovieLens-1M datasets are used for performance testing of comparative experiments. -
MovieLens dataset
The MovieLens dataset contains questions answerable using Wikidata as the knowledge graph, focusing on questions with a single entity and relation. -
Gowalla, Yelp, and ML-1M
The dataset used in this paper is Gowalla, Yelp, and ML-1M. Gowalla is a social media platform with 210,537 users and 100,000 items. Yelp is a review website with 1,000,209... -
End-to-End User Behavior Retrieval in Click-Through Rate Prediction Model
Click-Through Rate (CTR) prediction is one of the core tasks in recommender systems (RS). It predicts a personalized click probability for each user-item pair. -
Neural Collaborative Filtering
The dataset is used for neural collaborative filtering, which is a type of collaborative filtering that uses neural networks to learn the relationships between users and items. -
MovieLens-1M and Amazon Cell Phone
MovieLens-1M and Amazon Cell Phone datasets are used for evaluation. -
Amazon
The dataset used in the paper is a series of datasets introduced in [46], comprising large corpora of product reviews crawled from Amazon.com. Top-level product categories on... -
Amazon review dataset
The Amazon review dataset is used for multi-source domain adaptation. It contains review texts and ratings of bought products. Products are grouped into categories. Following... -
Self-Attentive Sequential Recommendation
The Steam-2M dataset is a large-scale dataset for game ratings. -
Synthetic Dataset
The dataset used in this work is a custom synthetic dataset generated using the liquid-dsp library, containing 600000 examples of each of 13.8 million examples, with SNRs... -
IJCAI-Contest Dataset
The IJCAI-Contest dataset is a real-world dataset with 17,435 users, 31,882 items, and 35,920 interactions. -
Tmall Dataset
The Tmall dataset is a real-world E-commerce dataset that contains multiple types of user behaviors including purchases and views.
