HHMF: hidden hierarchical matrix factorization for recommender systems

Data Mining and Knowledge Discovery, pp. 1548-1582, 2019.

Cited by: 4|Views54
EI

Abstract:

Matrix factorization (MF) is one of the most powerful techniques used in recommender systems. MF models the (user, item) interactions behind historical explicit or implicit ratings. Standard MF does not capture the hierarchical structural correlations, such as publisher and advertiser in advertisement recommender systems, or the taxonomy ...More

Code:

Data:

Upload PDF

1.Your uploaded documents will be check within 24h, and coins will be credited to your account.

2.As the current system does not support cash withdrawal, you can add staff WeChat (AMxiaomai) to receive it as a red packet.

3.10 coins will be exchanged for 1 yuan.

?

Upload a single paper

for 5 coins

Wechat's Red Packet
?

Upload 50 articles

for 250 coins

Wechat's Red Packet
?

Upload 200 articles

for 1000 coins

Wechat's Red Packet
?

Upload 500 articles

for 2500 coins

Wechat's Red Packet
?

Upload 1000 articles

for 5000 coins

Wechat's Red Packet
Your rating :
0

 

Tags
Comments