12 datasets found

The Beauty dataset is a product review dataset crawled from Amazon. The data is split into separate datasets by the top-level product category.

The dataset used in the paper for continuous-time sequential recommendation task

The dataset is used for sequential recommendation tasks, and it contains user-item interaction history.

Precise user modeling is critical for online personalized recommen-der services. Generally, users’ interests are diverse and are not limited to a single aspect, which is...

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...

The dataset used in this paper is a large-scale dataset for implicit feedback, consisting of user-item interactions, where each interaction is a pair of a user and an item.

Yelp-2018 dataset is a real-world dataset for recommender systems, containing user-item interactions.

Amazon-Toys-and-Games dataset is a real-world dataset for recommender systems, containing user-item interactions.

Amazon-Beauty dataset is a real-world dataset for recommender systems, containing user-item interactions.

Amazon-Video dataset is a dataset of user-item interactions from the Amazon video streaming service, which is used for evaluating the performance of recommendation algorithms.

Last.fm-1week dataset is a dataset of user-item interactions from the Last.fm music streaming service, which is used for evaluating the performance of recommendation algorithms.

The Yelp Dataset contains 1.6M reviews and 500K tips by 366K users for 61K businesses; 481K business attributes, such as hours, parking availability, ambience; and check-ins for...