The Solution of Cold Start Problem in Recommender System Introduction

Yuding Liu

doi:10.47297/taposatWSP2633-456908.20230401

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The Solution of Cold Start Problem in Recommender System Introduction

4卷第1期

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The Solution of Cold Start Problem in Recommender System Introduction
The Solution of Cold Start Problem in Recommender System Introduction
International school, Wuhan University of Science and Technology,Hubei,Wuhan,P.R. China,420000
2023年4卷第1期页码：48-54
DOI：10.47297/taposatWSP2633-456908.20230401

Full txt

(2023). The Solution of Cold Start Problem in Recommender System Introduction. 科技理论与实践（英文版）, 4(1), 48-54.

Yuding Liu. (2023). The Solution of Cold Start Problem in Recommender System Introduction. Theory and Practice of Science and Technology, 4(1), 48-54.
(2023). The Solution of Cold Start Problem in Recommender System Introduction. 科技理论与实践（英文版）, 4(1), 48-54. DOI： 10.47297/taposatWSP2633-456908.20230401.

Yuding Liu. (2023). The Solution of Cold Start Problem in Recommender System Introduction. Theory and Practice of Science and Technology, 4(1), 48-54. DOI： 10.47297/taposatWSP2633-456908.20230401.

摘要

Abstract

As big data time is coming

it is harder for us to find the information we need. In this situation

the recommendation systems are getting more attention. Collaborative filtering

matrix segmentation

graph neural network or several kinds of mixed use and other algorithms are applied to the recommendation system and achieved quite good results. However

most recommendation systems are faced with the cold start problem caused by insufficient data of new users. The cold start problem is very important

especially when the new system is born

all users of the system lack data

which makes the cold start problem particularly prominent. This study summarizes the various methods currently used to solve the cold start problem of recommender systems

makes recommendations for the characteristics of each method

and explores the potential impact of the combination of these methods on improving the performance of recommender systems. The innovation of this study lies in the comprehensive and in-depth analysis of the characteristics of different methods

and the suggestions for their combination

which provides new ideas and methods for solving the cold start problem.

关键词

Keywords

Recommender systemsCold startedData sparsity

references

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