Proceedings of the 2nd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2023)

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Comparative Studies on Modeling Users’ Multifaceted Interest Correlation for Social Recommendation

Authors
Yuchen Xiong1, *
1Jinan University, Jinan University-University of Birmingham Joint Institute, Guangzhou, China
*Corresponding author. Email: xyc1164001894@stu2020.jnu.edu.cn
Corresponding Author
Yuchen Xiong
Available Online 10 August 2023.
DOI
10.2991/978-94-6463-198-2_137How to use a DOI?
Keywords
Social recommender systems; social recommendation
Abstract

Recommender systems are essential for providing online users with items that might interest them. The research work of this paper is mainly classified into three aspects, one is based on the classification of research questions, one is based on the classification of research methods, and one is based on the classification of measures. The main techniques used in social recommender systems are the memory-based method and the model-based method. The aims of research papers are divided into increasing the accuracy of prediction and improving the performance of recommendations. In the classification of research methods, there are Content-based, Collaborative Filtering, and Hybrid Methods. And the output of these recommender systems can be divided into the value of the ratings and top-N items. The measurement methods mainly focus on the quality of prediction and the quality of the set. Finally, this paper also suggests feasible future research directions for the readers.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2nd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2023)
Series
Atlantis Highlights in Computer Sciences
Publication Date
10 August 2023
ISBN
10.2991/978-94-6463-198-2_137
ISSN
2589-4900
DOI
10.2991/978-94-6463-198-2_137How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Yuchen Xiong
PY  - 2023
DA  - 2023/08/10
TI  - Comparative Studies on Modeling Users’ Multifaceted Interest Correlation for Social Recommendation
BT  - Proceedings of the 2nd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2023)
PB  - Atlantis Press
SP  - 1317
EP  - 1328
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-198-2_137
DO  - 10.2991/978-94-6463-198-2_137
ID  - Xiong2023
ER  -