In order to transform the raw data file into our atomic files, we have collected 28
released the scripts for formatting these datasets into atomic files, detailed in RecSysDatasets. Meanwhile, we have uploaded the
processed atomic files in network disks with the links Google Drive and Baidu Wangpan (Password: e272).
||Rating [-1, 1-10]
||Rating [-10, 10]
||Rating [0, 100]
||Click [0, 1]
||income>=50k [0, 1]
A brief introduction of these datasets is as follows:
- Amazon: This dataset
reviews and metadata from Amazon, including 142.8 million reviews spanning May 1996 - July
2014. This dataset includes rating data (ratings), product metadata (descriptions, category
information, price, brand, and image features), and links (also viewed/also bought graphs).
dataset was collected from Epinions.com, a popular online consumer review website.
- Yelp :This dataset was collected
The Yelp dataset is a subset of the businesses, reviews, and user data for use in personal,
educational, and academic purposes.
- Tmall :
is provided by Ant Financial Services, used in the IJCAI16 contest.
- DIGINETICA :
includes user sessions extracted from an e-commerce search engine logs, with anonymized user
IDs, hashed queries, hashed query terms, hashed product descriptions and meta-data,
log-scaled prices, clicks, and purchases.
- YOOCHOOSE : This
been constructed by YOOCHOOSE GmbH to support participants in the RecSys Challenge 2015.
has been collected from a real-world ecommerce website. It is raw data, i.e. without any
content preprocessing, however, all values are hashed due to confidential issues.
dataset contains a Chinese grocery store transaction data from November 2000 to February
dataset was collected from Criteo, which consists of a portion of Criteo's traffic over
a period of several days.
This dataset is
used in Avazu CTR prediction contest.
- iPinYou: This dataset was
provided by iPinYou,
which contains all training datasets and leaderboard testing datasets of the three
seasons iPinYou Global RTB (Real-Time Bidding) Bidding Algorithm Competition.
This dataset contains check-ins in NYC and Tokyo collected for about 10 months. Each
check-in is associated with its time stamp, its GPS coordinates and its semantic
is from a location-based social networking website where users share their locations
by checking-in, and contains a total of 6,442,890 check-ins of these users over the
period of Feb. 2009 - Oct. 2010.
Research has collected and made available rating datasets from their movie web
This is the official data set used in the Netflix Prize competition.
Douban Movie is a Chinese website that allows Internet users to share their
comments and viewpoints about movies. This dataset contains more than 2 million
short comments of 28 movies in Douban Movie website.
This dataset contains social networking, tagging, and music artist listening information from a
set of 2K users from Last.fm online music system.
This dataset contains more than one billion music listening events created by more than 120,000
users of Last.fm. Each listening event is characterized by artist, album, and track name, and
includes a timestamp.
Music: This dataset represents a snapshot of the Yahoo! Music community's preferences
for various musical artists.
This dataset was collected by Cai-Nicolas Ziegler in a 4-week crawl (August / September 2004)
from the Book-Crossing community with kind permission from Ron Hornbaker, CTO of Humankind
Systems. Contains 278,858 users (anonymized but with demographic information) providing
1,149,780 ratings (explicit / implicit) about 271,379 books.
This dataset is reviews and game information from Steam, which contains 7,793,069 reviews,
2,567,538 users, and 32,135 games. In addition to the review text, the data also includes the
users' play hours in each review.
This dataset contains information on user preference data from myanimelist.net. Each user is
able to add anime to their completed list and give it a rating and this data set is a
compilation of those ratings.
This dataset is originally constructed by paper Learning image and user features for
recommendations in social networks for evaluating content-based image recommendation,
and processed by paper Neural Collaborative Filtering.
This dataset contains anonymous ratings of jokes by users of the Jester Joke Recommender System.
This dataset was released in KDD Cup 2010 Educational Data Mining Challenge, which contains
the situations of students submitting exercises on the systems.
Websites: This dataset contains 30 features of 11,055 websites and labels of
whether they are phishing websites or not. The websites' features include 12 address-bar based
This dataset is extracted by Barry Becker from the 1994 Census database, which
consists of a list of people's attributes and whether they make over 50k a year.
This dataset is a large-scale dataset for news recommendation research. It was collected from
anonymized behavior logs of Microsoft News website. MIND contains about 160k English news
articles and more than 15 million impression logs generated by 1 million users.