Work

Novelty and Diversity in Top-N Recommendation -- Analysis and Evaluation

Year: 2011

Type: article

Source: ACM Transactions on Internet Technology

DOI: 10.1145/1944339.1944341

Authors: Neil Hurley, Mi Zhang

Institutions: University College Dublin, Fudan University

Language: English

Topic: Recommender Systems and Techniques

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: closed

Funders: Science Foundation Ireland, Ministry of Science and Technology of the People's Republic of China, Shanghai Leading Academic Discipline Project

Awards: G267029097, G5819912606, Secure and Trustworthy Personalisation for E-commerce

OpenAlex ID: W1967787801

FWCI: 20.11

Cites: 28

Cited by: 323

Related to: 10