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Recommendation Systems
A recommendation system is a technology that leverages user behavior data, preference information, and item features to predict users' interest in items through algorithmic models. Its core objective is to optimize the user experience, enhance user satisfaction and platform stickiness, while also increasing business conversion rates and revenue. Recommendation systems are widely used in e-commerce, social media, online video, and music streaming platforms, among others, to effectively match user needs with platform resources, achieving efficient information filtering and value delivery.
MovieLens 1M
SSE-PT
MovieLens 20M
HyperML
MovieLens 100K
GHRS
MovieLens 10M
scaled-CER
Amazon-Book
HSTU+MoL
Gowalla
NESCL
Yelp2018
NESCL
Netflix
H+Vamp Gated
Douban Monti
GLocal-K
ReDial
KERL
Million Song Dataset
EASE
Flixster Monti
IGMC
Douban
I-CFN
Amazon Games
CARCA
YahooMusic Monti
MG-GAT
Amazon Beauty
ProxyRCA
Amazon Fashion
SAERS
Flixster
TransCF
Epinions
DANSER
YahooMusic
GRALS
Amazon Men
CARCA Learnt + Con
Polyvore
Fashion GAE
Last.FM
Ekar*
Yelp
ConvNCF
Frappe
INN
DBbook2014
KTUP (soft)
WeChat
DANSER
Amazon Product Data
TLSAN
Book-Crossing
KGNN-LS
Amazon-CDs
HGN
LT-OCF
MovieLens-Latest
RATE-CSE
Epinions-Extend
PixelRec
SASRec
Amazon C&A
Dianping-Food
KGNN-LS
GoodReads-Children
HGN
Amazon Books
Multi-Gradient Descent
Echonest
Tradesy
Amazon-Movies
HetroFair
Delicious
Amazon-Health
BeerAdvocate
CFM
Steam
SASRec
Alibaba-iFashion
HAKG
Pinterest
Amazon-Beauty
Fashion-Similar
SR-PredAO(SGNN-HN)
Last.FM-360k
GoodReads-Comics
HGN
Declicious
TransCF
CiteULike
Ciao
Amazon-Electronics