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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.

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Metadaten
Author of HS ReutlingenRätsch, 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 and Francis
Place of publication:London
Document Type:Article
Language:English
Year of Publication: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):License Logo  Creative Commons - CC BY - Namensnennung 4.0 International