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基于流行的推荐研究综述

雷钦岚 田萱

计算机科学与探索2024,Vol.18Issue(5):1109-1134,26.
计算机科学与探索2024,Vol.18Issue(5):1109-1134,26.DOI:10.3778/j.issn.1673-9418.2309016

基于流行的推荐研究综述

Survey on Popularity Based Recommendation

雷钦岚 1田萱1

作者信息

  • 1. 北京林业大学 信息学院,北京 100083||国家林业草原林业智能信息处理工程技术研究中心,北京 100083
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摘要

Abstract

Currently,popularity based recommendation has become a research hotspot.The use of popularity consid-erably improves the recommendation effects,while the Matthew effect caused by popularity bias has also garnered extensive attention among researchers.Some researchers consider combining both aspects to produce hybrid popu-larity based recommendation.Adopting the concept of popularity,a unified representation of popularity,popularity bias,and hybrid popularity is provided in this paper.Firstly,the background of popularity in the field of recommen-dation is introduced.Then,based on different perspectives,a comprehensive survey on popularity-enhanced recom-mendation methods,popularity debias recommendation methods,and hybrid popularity based recommendation methods is provided.Each type of method is further subdivided in specific subtasks of modeling or concrete strate-gies.The representative models of each method are introduced and analyzed,and their advantages and limitations are evaluated.The mechanisms and applicable scenarios of each method are also summarized in detail.Furthermore,the commonly used datasets,performance evaluation indicators and baseline are introduced.A comparative analysis of the representative methods performance is also listed.Finally,some opinions on the trends of popularity based recommendation are presented.An outlook on the technical difficulties and hotspots for future development from multiple perspectives is analyzed and predicted.

关键词

流行度/流行偏差/混合式流行/基于流行的推荐

Key words

popularity/popularity bias/hybrid popularity/popularity based recommendation

分类

信息技术与安全科学

引用本文复制引用

雷钦岚,田萱..基于流行的推荐研究综述[J].计算机科学与探索,2024,18(5):1109-1134,26.

基金项目

国家重点研发计划(2018YFC1603302,2018YFC1603305). This work was supported by the National Key Research and Development Program of China(2018YFC1603302,2018YFC1603305). (2018YFC1603302,2018YFC1603305)

计算机科学与探索

OA北大核心CSTPCD

1673-9418

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