61 datasets found

Amazon-book dataset, Yelp dataset, and ML-1M dataset.

Last.FM is a dataset containing musician listening information from a set of 2 thousand users from Last.fm online music system.

TikTok 2 and WechatMoments are real-world datasets used for evaluating the proposed CrossDistil framework.

The dataset used in the paper is Amazon Books, Amazon Toys, and Retailrocket.

This dataset contains the pickup, drop-off timestamps and pickup, drop-off locations of taxis in New York city from 1st Jan 2019 to 28th Feb 2019.

The dataset used in the paper is MovieLens-1M and Tmall.

The Amazon Reviews dataset is used to predict the usefulness of Amazon reviews using off-the-shelf argumentation mining.

The associated task is to predict the movie rating on a 5-star scale. This dataset contains 6,040 users, 3,900 movies, and 1,000,209 ratings, i.e., rating matrix is 4.26% full.

The dataset used in the paper is a large-scale graph dataset, consisting of users and shows with multi-attribute edges. The graph is constructed by selecting user IDs and side...

CiteULike is a user-article dataset, where each article has a 300-dimension tf-idf vector. XING is a user-view-job dataset where each job is described by a 2738-dimension...

The dataset used in the paper is MovieLens-1M, MovieLens-10M, and BookCrossing.

The dataset used in the paper is Taobao2014, Taobao2015, Alibaba and Amazon. The dataset is used for implicit recommendation and contains user-item interactions.

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...

The dataset used in the paper is a large-scale recommendation system dataset, where each item or user may correspond to a separate bandit arm.

FashionCLIP is a large model built for fashion, used to introduce GradREC, a new type of recommendation experience.

A novel Markov decision process (MDP)-based re-ranking model for final-stage recommendation, called Panel-MDP.

The Amazon Review dataset is a widely used benchmark dataset for cross-domain sentiment analysis.

The Book-Crossing dataset is a book rating dataset that contains rating records of books by users from the Book-Crossing community.

Office dataset consists of 31 categories and contains around 4,700 images across three domains, namely Amazon(A), DSLR(D) and Webcam(W).

The dataset used in the paper is a user-item bipartite graph, where each user and item is represented as a node, and the edges between them represent the interactions between...