45 datasets found

Graph learning based recommender systems: A review

A survey on graph-based recommender systems

A deep framework for cross-domain and cross-system recommendations

A graph-based framework for cross-domain and cross-system recommendations

A unified framework for cross-domain and cross-system recommendations

Decentralized Multi-Target Cross-Domain Recommendation for Multi-Organization Collaborations

The proposed time aware cross-network recommender solution transfers auxiliary user interaction information from source networks to a target network and provides recommendations...

Typical large-scale recommender systems use deep learning models that are stored on a large amount of DRAM. These models often rely on embeddings, which consume most of the...

MovieLens 1 Million Dataset is a large-scale movie recommendation dataset, which contains 6040 users and 3706 items.

The dataset used in this paper is the MovieLens 1M dataset, which contains a 1M 1-5 star ratings by 6,040 users for 3,952 movies.

The MovieLens-100K and MovieLens-ml-latest-small datasets are used to evaluate the effectiveness of the proposed detection method.

The dataset is a two-mode tensor depicting binary (user, anime) preferences. The tensor contains 1, 300, 160 observed entries, of size 25, 838 × 4, 066.

A dataset of movie ratings, a dataset of anime ratings.

The Amazon dataset is used to evaluate the performance of the proposed approach. It consists of 2000 users, 1500 items, 86690 reviews, 7219 number ratings, 3.6113 average number...

A dataset for interactive recommender systems, used to evaluate the proposed Tree-structured Policy Gradient Recommendation (TPGR) framework.

The Epinions dataset is a large-scale opinion mining dataset. It contains 1 million user-item interactions and is widely used for evaluating the performance of recommender systems.

Knowledge graphs are composed of different elements: entity nodes, relation edges, and literal nodes. Each literal node contains an entity’s attribute value (e.g. the height of...

DiffRec, L-DiffRec, and T-DiffRec datasets.

Diffusion Recommender Model, which infers users’ interaction probabilities in a denoising manner.

The MovieLens100K and MovieLens1M datasets are used to evaluate the proposed method.