66 datasets found

The Coat dataset is a dataset of user ratings on coats. The dataset is used to evaluate the performance of the proposed Epsilon Non-Greedy framework.

The dataset used in the paper is a combination of two datasets: YahooR3 and Coat. The dataset is used to evaluate the performance of the proposed Epsilon Non-Greedy framework.

PAKDD Recobell dataset, Instacart dataset

MovieLens-100K, Steam-200K, Gowalla datasets used for federated recommender system experiments

The dataset used in this paper for approximate nearest neighbor search.

Three recommendation datasets for evaluation: MovieLens-20M, Last.fm hetrec-2011, and LibraryThing.

Three recommendation datasets for evaluation: MovieLens-20M, Last.fm hetrec-2011, and LibraryThing.

Three recommendation datasets for evaluation: MovieLens-20M, Last.fm hetrec-2011, and LibraryThing.

Two real-world datasets for evaluation of PipAttack, namely MovieLens-1M and Amazon.

Two popular and publicly accessible datasets: MovieLens (ML) and Amazon Digital Music (AZ).

The Taobao User Behavior dataset is a subset of user behaviors on Taobao collected within 9 days and consists of more than 70 million samples and 1 million users.

FourSquare shopping places dataset from 5 cities in Indonesia. It consists of 1) 176 shopping places data, 2) 3844 visitors' reviews, and 3) 14309 users data.

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

The dataset used in the paper is a Netflix dataset, which is a large-scale matrix factorization problem.

Bing-News is a dataset containing 1,025,192 pieces of implicit feedback collected from the server logs of Bing News.

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...

Amazon book data set contains book reviews and metadata from Amazon. Following previous work, we regard reviews as positive samples and randomly select products not rated by a...

The production data set collected from Alibaba display advertising platform. We randomly select about 1% of 1-day samples for training and 0.1% of the next-day samples for...

Location prediction forecasts a user’s location based on historical user mobility traces. To tackle the intrinsic sparsity issue of real-world user mobility traces,...

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...