124 datasets found

CiteULike-T is a large-scale article recommendation dataset.

Steam-200k is a large-scale game recommendation dataset.

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

A public dataset with a coupons website, suitable for evaluating the proposed methodology.

The dataset is a user-item interaction graph, with 1 billion users and tens of million items.

A conversational recommendation dataset released by Kang et al. This dataset was constructed using ParlAI to interface with Amazon Mechanical Turk (AMT) to reflect the movie...

The dataset used in the paper is Alipay, Tmall, and Alimama. These datasets are used for click-through rate (CTR) prediction. The datasets contain user and item features, as...

The dataset used in the paper is Alipay, Tmall, and Alimama. These datasets are used for click-through rate (CTR) prediction. The datasets contain user and item features, as...

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

The dataset used in the paper is a real-life dataset from education testing, recommendation systems, and finance. It contains user-item binary response data.

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.

The DBbook2014 dataset is a book recommendation dataset, which contains 5,576 users, 2,680 items, and 65,961 ratings.

Ali-CCP5 is a public click-through rate prediction dataset collected from traffic logs of Taobao's RS, consisting of 85 million samples.

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

The dataset is a large-scale industrial dataset collected from Kuaishou, containing user interaction data with click-through as labels. The dataset has a maximum history length...