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

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H&M Personalized Fashion Product Recommendation Using LightgbmRanker

Authors
Dan Xian1, Shaozan Cui2, Bo Wang3, Lishuai Cui4, *
1Northeastern University, San Jose, USA
2Nanjing University of Finance & Economics, Shanghai, China
3College of Information and Electrical Engineering, China Agricultural University, Beijing, China
4King’s College London, London, UK
*Corresponding author. Email: lishuai.cui@kcl.ac.uk
Corresponding Author
Lishuai Cui
Available Online 10 August 2023.
DOI
10.2991/978-94-6463-198-2_23How to use a DOI?
Keywords
recommendation system; LightGBM Ranker; MAP; feature engineering
Abstract

The product recommendation system is a system that analyzes user preferences, searches for a large number of product information in the e-mall, and recommends products that may be of interest to users, providing an intelligent shopping experience for online shopping users. It can help users more accurately and quickly discover interesting and high-quality product information, enhance the value of information, and improve the user’s online shopping experience. In this article, we use data provided by H&M to construct a recommendation system using LightgbmRanker. To evaluate our experiment’s performance, we do compared competitions. We use map as the evaluation metric. The result shows that our LightgbmRanker owns the highest 0.0282 among these models, which is 0.063, 0.056 higher than SVD, TF recommender respectively.

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
978-94-6463-198-2
ISSN
2589-4900
DOI
10.2991/978-94-6463-198-2_23How 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  - Dan Xian
AU  - Shaozan Cui
AU  - Bo Wang
AU  - Lishuai Cui
PY  - 2023
DA  - 2023/08/10
TI  - H&M Personalized Fashion Product Recommendation Using LightgbmRanker
BT  - Proceedings of the 2nd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2023)
PB  - Atlantis Press
SP  - 201
EP  - 208
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-198-2_23
DO  - 10.2991/978-94-6463-198-2_23
ID  - Xian2023
ER  -