Improving top-<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si2.svg" display="inline" id="d1e1427"><mml:mi>N</mml:mi></mml:math> recommendations using batch approximation for weighted pair-wise loss-Reference-Cited by-同舟云学术

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Improving top-N recommendations using batch approximation for weighted pair-wise loss

Published:2024-03 Issue: Volume:15 Page:100520
ISSN:2666-8270
Container-title:Machine Learning with Applications
language:en
Short-container-title:Machine Learning with Applications

Author:

Aftab Sofia^ORCID,Ramampiaro Heri

Publisher

Elsevier BV

Subject

General Earth and Planetary Sciences,General Environmental Science

Reference54 articles.

1. Towards time-dependant recommendation based on implicit feedback;Baltrunas,2009

2. The architecture and datasets of Docear’s Research paper recommender system;Beel;D-Lib Magazine,2014

3. From RankNet to LambdaRank to LambdaMART: An overview;Burges,2010

4. From RankNet to LambdaRank to LambdaMART: An overview;Burges;Learning,2010

5. Learning to rank with nonsmooth cost functions;Burges,2007

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