The MovieLens datasets, first released in 1998, describe people’s expressed preferences for movies. These preferences take the form of tuples, each the result of a person expressing a preference (a 0-5 star rating) for a movie at a particular time. These preferences were entered by way of the MovieLens web site1 — a recommender system that asks its users to give movie ratings in order to receive personalized movie recommendations.
1,244 PAPERS • 19 BENCHMARKS
Gowalla is a location-based social networking website where users share their locations by checking-in. The friendship network is undirected and was collected using their public API, and consists of 196,591 nodes and 950,327 edges. We have collected a total of 6,442,890 check-ins of these users over the period of Feb. 2009 - Oct. 2010.
203 PAPERS • 5 BENCHMARKS
The Yelp Dataset is a valuable resource for academic research, teaching, and learning. It provides a rich collection of real-world data related to businesses, reviews, and user interactions. Here are the key details about the Yelp Dataset: Reviews: A whopping 6,990,280 reviews from users. Businesses: Information on 150,346 businesses. Pictures: A collection of 200,100 pictures. Metropolitan Areas: Data from 11 metropolitan areas. Tips: Over 908,915 tips provided by 1,987,897 users. Business Attributes: Details like hours, parking availability, and ambiance for more than 1.2 million businesses. Aggregated Check-ins: Historical check-in data for each of the 131,930 businesses.
86 PAPERS • 24 BENCHMARKS
KuaiRand is an unbiased sequential recommendation dataset collected from the recommendation logs of the video-sharing mobile app, Kuaishou (快手). It is the first recommendation dataset with millions of intervened interactions of randomly exposed items inserted in the standard recommendation feeds!
42 PAPERS • 1 BENCHMARK
Amazon Review is a dataset to tackle the task of identifying whether the sentiment of a product review is positive or negative. This dataset includes reviews from four different merchandise categories: Books (B) (2834 samples), DVDs (D) (1199 samples), Electronics (E) (1883 samples), and Kitchen and housewares (K) (1755 samples).
35 PAPERS • 7 BENCHMARKS
This dataset includes reviews (ratings, text, helpfulness votes), product metadata (descriptions, category information, price, brand, and image features), and links (also viewed/also bought graphs).
18 PAPERS • 3 BENCHMARKS
This datasets is a subset of the Amazon reviews dataset which contain Men related products
14 PAPERS • 2 BENCHMARKS
Amazon-Sports is a sub-category of the Amazon dataset, which contains a series of product reviews crawled from Amazon.com.
14 PAPERS • 1 BENCHMARK
an image cover dataset in short video recommendation
1 PAPER • 1 BENCHMARK
The datasets of "Time Interval-enhanced Graph Neural Network for Shared-account Cross-domain Sequential Recommendation" (TNNLs 2022)
1 PAPER • NO BENCHMARKS YET
X-Wines is a consistent wine dataset containing 100,646 instances and 21 million real evaluations carried out by users. Data were collected on the open Web in 2022 and pre-processed for wider free use. They refer to the scale 1–5 ratings carried out over a period of 10 years (2012–2021) for wines produced in 62 different countries.
0 PAPER • NO BENCHMARKS YET