Learning personalized item-to-item recommendation metric via implicit feedback

Year
2022
Direct or indirect related to Private Intelligence
INDIRECT
Link
https://scholar.google.com/citations?view_op=view_citation&hl=en&user=E-kZZeQAAAAJ&cstart=20&pagesize=80&citation_for_view=E-kZZeQAAAAJ:blknAaTinKkC
Conference/Journal

International conference on artificial intelligence and statistics, 1062-1077

Author(s) from Distilled Foundation
TN Hoang
How the work relates to Private Intelligence

Gained Experience

Investigating a personalizable deep metric model that captures both the internal contents of items and how they were interacted with by users.