A Study on Input Methods of User Preference for Personalized Fashion Coordinate Recommendations

被引:2
作者
Hattori, Shun [1 ]
Miyamoto, Shohei [1 ]
Sunayama, Wataru [1 ]
Takahara, Madoka [2 ]
机构
[1] Univ Shiga Prefecture, Hikone, Japan
[2] Ryukoku Univ, Otsu, Shiga, Japan
来源
HUMAN INTERFACE AND THE MANAGEMENT OF INFORMATION, PT III, HIMI 2024 | 2024年 / 14691卷
关键词
Preference Input Methods; Fashion Coordinates; Personalization; Recommender Systems; CLIP; Text-to/from-Image;
D O I
10.1007/978-3-031-60125-5_12
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
In most of the existing researches and practical e-commerce services for fashion coordinate recommendations, only one of various input methods of a user's preference has been adopted without enough arguments. Therefore, this paper conducts a deeper study on various input methods of a user's preference for personalized fashion coordinate recommendations, comprehensively by two kinds of questionnaire investigation: how well do you think that you have expressed your preference to a recommender system of fashion coordinates via an input method? and how well has a recommender system recommended fashion coordinates for you based on your preference expressed via an input method?.
引用
收藏
页码:178 / 196
页数:19
相关论文
共 44 条
  • [31] A study of user profile representation for personalized cross-language information retrieval
    Zhou, Dong
    Lawless, Seamus
    Wu, Xuan
    Zhao, Wenyu
    Liu, Jianxun
    ASLIB JOURNAL OF INFORMATION MANAGEMENT, 2016, 68 (04) : 448 - 477
  • [32] A Qualitative Evaluation of User Preference for Link-Based vs. Text-Based Recommendations of Wikipedia Articles
    Ostendorff, Malte
    Breitinger, Corinna
    Gipp, Bela
    TOWARDS OPEN AND TRUSTWORTHY DIGITAL SOCIETIES, ICADL 2021, 2021, 13133 : 63 - 79
  • [33] Interactive user Modeling for personalized access to museum collections: The rijksmuseum case study
    Wang, Yiwen
    Aroyo, Lora M.
    Stash, Natalia
    Rutledge, Lloyd
    USER MODELING 2007, PROCEEDINGS, 2007, 4511 : 385 - +
  • [34] A Comparative Study of Preference Ordering Methods for Multi-Criteria Ranking
    Zheng, Yong
    Wang, David
    2023 10TH IEEE SWISS CONFERENCE ON DATA SCIENCE, SDS, 2023, : 108 - 111
  • [35] User Recommendations in Reciprocal and Bipartite Social Networks-An Online Dating Case Study
    Zhao, Kang
    Wang, Xi
    Yu, Mo
    Gao, Bo
    IEEE INTELLIGENT SYSTEMS, 2014, 29 (02) : 27 - 35
  • [36] Application of personalized federated learning methods to environmental sound classification: A comparative study
    Xu, Huaxing
    Fan, Zeng
    Liu, Xudong
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2024, 135
  • [37] A personalized mobile app for physical activity: An experimental mixed-methods study
    Tong, Huong Ly
    Quiroz, Juan C.
    Kocaballi, Ahmet Baki
    Ijaz, Kiran
    Coiera, Enrico
    Chow, Clara K.
    Laranjo, Liliana
    DIGITAL HEALTH, 2022, 8
  • [38] Quantitative Analysis of Training Methods, Data Size, and User-Specific Effectiveness in DL-Based Personalized Aesthetic Evaluation
    Abe, Yoshia
    Daikoku, Tatsuya
    Kuniyoshi, Yasuo
    PRICAI 2024: TRENDS IN ARTIFICIAL INTELLIGENCE, PT I, 2025, 15281 : 3 - 15
  • [39] A Comparative Study of Feature Extraction Methods from User Reviews for Recommender Systems
    Bhagat, Pradnya
    Pawar, Jyoti D.
    PROCEEDINGS OF THE ACM INDIA JOINT INTERNATIONAL CONFERENCE ON DATA SCIENCE AND MANAGEMENT OF DATA (CODS-COMAD'18), 2018, : 325 - 328
  • [40] An empirical study on user-topic rating based collaborative filtering methods
    Tieke He
    Zhenyu Chen
    Jia Liu
    Xiaofang Zhou
    Xingzhong Du
    Weiqing Wang
    World Wide Web, 2017, 20 : 815 - 829