31 datasets found

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.

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

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

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 MovieLens 1 Million Dataset and LDOS-CoMoDa Dataset

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 a collection of implicit interactions gathered from various sources, including social networks and online communities.

The dataset used in the paper is a collection of explicit interactions gathered from various sources, including music websites, movie ratings, book clubs, social networks, and...

The dataset used in the paper is a collection of implicit interactions gathered from various sources, including music websites, movie ratings, book clubs, social networks, and...

Movielens-100k dataset is a network of user-movie ratings

The dataset used in the paper is the Yelp Challenge Dataset and the IMDB corpus of movie reviews.

The dataset used in the paper is a collection of explicit interactions gathered from various sources, including music websites, movie ratings, book clubs, social networks, and...

The dataset consists of data from seven participants whose response times ranged from 4 to 429 seconds. The dataset includes information about the participant, the response...

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