Time Matters: Sequential Recommendation with Complex Temporal Information

Wenwen Ye
Wenwen Ye
Shuaiqiang Wang
Shuaiqiang Wang
Xuepeng Wang
Xuepeng Wang

SIGIR '20: The 43rd International ACM SIGIR conference on research and development in Information Retrieval Virtual Event China July, 2020, pp. 1459-1468, 2020.

Cited by: 0|Bibtex|Views95|DOI:https://doi.org/10.1145/3397271.3401154
EI
Other Links: dl.acm.org|dblp.uni-trier.de|academic.microsoft.com

Abstract:

Incorporating temporal information into recommender systems has recently attracted increasing attention from both the industrial and academic research communities. Existing methods mostly reduce the temporal information of behaviors to behavior sequences for subsequently RNN-based modeling. In such a simple manner, crucial time-related si...More

Code:

Data:

Your rating :
0

 

Tags
Comments