Work

PURS: Personalized Unexpected Recommender System for Improving User Satisfaction

Year: 2020

Type: conference-paper

Source: ACM Conference on Recommender Systems (RecSys)

DOI: 10.1145/3383313.3412238

Authors: Pan Li, Maofei Que, Zhichao Jiang, YAO HU, Alexander Tuzhilin

Institutions: New York University, Alibaba Group (China)

Language: English

Topic: Recommender Systems and Techniques

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: closed

OpenAlex ID: W3088072029

FWCI: 5.27

Cites: 45

Cited by: 63

Related to: 10