Personalized clothing recommendation based on user emotional analysis
- With the continuous development of economy, consumers pay more attention to the demand for personalization clothing. However, the recommendation quality of the existing clothing recommendation system is not enough to meet the user’s needs. When browsing online clothing, facial expression is the salient information to understand the user’s preference. In this paper, we propose a novel method to automatically personalize clothing recommendation based on user emotional analysis. Firstly, the facial expression is classified by multiclass SVM. Next, the user’s multi-interest value is calculated using expression intensity that is obtained by hybrid RCNN. Finally, the multi-interest value is fused to carry out personalized recommendation. The experimental results show that the proposed method achieves a significant improvement over other algorithms.
| Author of HS Reutlingen | Rätsch, Matthias |
|---|---|
| URN: | urn:nbn:de:bsz:rt2-opus4-30648 |
| DOI: | https://doi.org/10.1155/2020/7954393 |
| ISSN: | 1026-0226 |
| eISSN: | 1607-887X |
| Erschienen in: | Discrete dynamics in nature and society : an international multidisciplinary research and review journal |
| Publisher: | Taylor & Francis |
| Place of publication: | London |
| Document Type: | Journal article |
| Language: | English |
| Publication year: | 2020 |
| Volume: | 2020 |
| Issue: | Cognitive Modeling of Multimodal Data Intensive Systems for Applications in Nature and Society (COMDICS) |
| Page Number: | 8 |
| First Page: | 1 |
| Last Page: | 8 |
| Article Number: | 7954393 |
| DDC classes: | 500 Naturwissenschaften und Mathematik |
| Open access?: | Ja |
| Licence (German): |  Creative Commons - CC BY - Namensnennung 4.0 International |
