Domain: Recommendation

Overview

Recommender systems or recommendation systems (sometimes replacing "system" with a synonym such as platform or engine) are a subclass of information filtering system that seek to predict the 'rating' or 'preference' that user would give to an item. Recommender systems have become extremely common in recent years, and are applied in a variety of applications. The most popular ones are probably movies, music, news, books, research articles, search queries, social tags, and products in general.

Dataset List

Dataset Descriptions This dataset is derived from the rating data of Movielens-10M (Movielens-10M), which contains 10000054 ratings applied to 10681 movies by 71567 users of the online movie recommender service MovieLens. All ratings are contained in the file ratings.dat, which the field ...
BASELINE RMSE P@1 P@2 P@3 P@4 P@5 MAP Evaluation
Item-based CF 0.7999 0.5572 0.5095 0.4715 0.4400 0.4124 0.5518 Detail
NMF 0.7975 0.5620 0.5125 0.4746 0.4426 0.4146 0.5554 Detail
SVD 0.7932 0.5625 0.5134 0.4749 0.4429 0.4149 0.5558 Detail
SVD++ 0.7842 0.5782 0.5260 0.4852 0.4512 0.4220 0.5653 Detail
BASELINE NDCG@1 NDCG@2 NDCG@3 NDCG@4 NDCG@5 MeanNDCG Evaluation
Item-based CF 0.6947 0.7020 0.7000 0.6834 0.6529 0.7726 Detail
NMF 0.7005 0.7062 0.7044 0.6874 0.6564 0.7768 Detail
SVD 0.7000 0.7066 0.7045 0.6875 0.6566 0.7768 Detail
SVD++ 0.7148 0.7191 0.7158 0.6979 0.6661 0.7856 Detail
Summary This dataset was constructed to support participants in the Netflix Prize. See http://www.netflixprize.com for details about the prize. The movie rating files contain over 100 million ratings from 480 thousand randomly-chosen, anonymous Netflix customers over 17 thousand movie titles. ...
BASELINE RMSE P@1 P@2 P@3 P@4 P@5 MAP Evaluation
BASELINE NDCG@1 NDCG@2 NDCG@3 NDCG@4 NDCG@5 MeanNDCG Evaluation
Yahoo! Webscope ReadMe The data included herein is provided as part of the Yahoo! Webscope program for use solely under the terms of a signed Yahoo! Data Sharing Agreement. Any publication using this data should attribute Yahoo!...
BASELINE RMSE P@1 P@2 P@3 P@4 P@5 MAP Evaluation
BASELINE NDCG@1 NDCG@2 NDCG@3 NDCG@4 NDCG@5 MeanNDCG Evaluation
DATASET DESCRIPTION Ta-Feng is a grocery shopping dataset released by ACM RecSys, it covers products from food, office supplies to furniture. The dataset collected users` transaction data of 4 months, from November 2000 to February 2001. The total count of transactions in this dataset is 817741...
BASELINE F1-Score HIT-RATIO MeanNDCG Evaluation
HRM 0.0620 0.2820 0.0890 Detail
Beiren is a real world large scale retail dataset in China, it records supermarket purchase histories during the period from 2012 to 2013, and contains 49,290,14949,290,149 transactions over 220,828220,828 items belonging to 1,206,3791,206,379 users. Here we release a part of users` purchase histo...
BASELINE hamming_loss wprecision wrecall wf1 Evaluation