Proceedings of the 2023 3rd International Conference on Business Administration and Data Science (BADS 2023)

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Hybrid Recommendation Algorithm for Intelligent Recommendation of Popular Stores for Agricultural E-commerce Platforms

Authors
Peng Li1, *
1Business School, Shandong Polytechnic College, Jining, Shandong, 272000, China
*Corresponding author. Email: 1261184813@protonmail.com
Corresponding Author
Peng Li
Available Online 30 December 2023.
DOI
10.2991/978-94-6463-326-9_12How to use a DOI?
Keywords
e-commerce platform; intelligent recommendation; collaborative filtering algorithm; fusion multi-attribute algorithm; system design
Abstract

With the increasing number of e-commerce platforms, each e-commerce platform has started to provide different intelligent recommendation services in order to dominate the market. However, in agricultural e-commerce platforms, the application of intelligent recommendation algorithms is less, resulting in a poor shopping experience for users. Therefore, the study proposes an agricultural e-commerce platform applying hybrid recommendation algorithms. The system achieves primary recommendation through to collaborative filtering algorithm to form a primary commodity recommendation set; then on the basis of the primary commodity recommendation set, secondary recommendation is carried out by fusing multi-attribute algorithms to obtain the final personalized recommendation results. After testing, the response time of each function of the system is short, and the stability and compatibility are good.

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 2023 3rd International Conference on Business Administration and Data Science (BADS 2023)
Series
Atlantis Highlights in Computer Sciences
Publication Date
30 December 2023
ISBN
978-94-6463-326-9
ISSN
2589-4900
DOI
10.2991/978-94-6463-326-9_12How 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  - Peng Li
PY  - 2023
DA  - 2023/12/30
TI  - Hybrid Recommendation Algorithm for Intelligent Recommendation of Popular Stores for Agricultural E-commerce Platforms
BT  - Proceedings of the 2023 3rd International Conference on Business Administration and Data Science (BADS 2023)
PB  - Atlantis Press
SP  - 119
EP  - 129
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-326-9_12
DO  - 10.2991/978-94-6463-326-9_12
ID  - Li2023
ER  -