Applied and Computational Engineering

- The Open Access Proceedings Series for Conferences


Proceedings of the 3rd International Conference on Signal Processing and Machine Learning

Series Vol. 4 , 30 May 2023


Open Access | Article

Application of recall methods in recommendation systems

Yumeng Wang * 1
1 Zhejiang University, Hangzhou, China

* Author to whom correspondence should be addressed.

Applied and Computational Engineering, Vol. 4, 44-51
Published 30 May 2023. © 30 May 2023 The Author(s). Published by EWA Publishing
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Citation Yumeng Wang. Application of recall methods in recommendation systems. ACE (2023) Vol. 4: 44-51. DOI: 10.54254/2755-2721/4/20230344.

Abstract

In order to have a more comprehensive introduction and understanding of the re-search progress of recall strategies in recommender systems, this paper reviews the application of diverse recall methods in various recommender systems by different researchers. By searching and reading literature in major databases like Google Scholar, it is found that the recall method suitable for news recommendation system is also generally applicable in other recommendation systems. Therefore, this paper takes news recommendation system as an example to introduce traditional content-based recall and collaborative filtering-based methods. Hot-based recall and Embed-ding-based recall also developed in recent years. Furthermore, recall strategies (emo-tion-based recall and UIBB) that are specifically applicable to music and e-commerce recommendation systems are introduced. This paper briefly introduces these recall styles and collects researchers' evaluations and attitudes towards these recall styles, aiming to provide help for recommender system designers in optimizing recall methods.

Keywords

Recommendation System, content-based Recall, Collaborative Filtering, Hot-based Recall, News Recommendation

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Data Availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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Volume Title
Proceedings of the 3rd International Conference on Signal Processing and Machine Learning
ISBN (Print)
978-1-915371-55-3
ISBN (Online)
978-1-915371-56-0
Published Date
30 May 2023
Series
Applied and Computational Engineering
ISSN (Print)
2755-2721
ISSN (Online)
2755-273X
DOI
10.54254/2755-2721/4/20230344
Copyright
30 May 2023
Open Access
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Copyright © 2023 EWA Publishing. Unless Otherwise Stated