Extracting Characteristics of Fashion Models from Magazines for Item Recommendation

被引：1

作者：

Murakami, Taishi ^{[1
]}

Kurosawa, Yoshiaki ^{[1
]}

Kurashita, Yuri ^{[1
]}

Mera, Kazuya ^{[1
]}

Takezawa, Toshiaki ^{[1
]}

机构：

[1] Hiroshima City Univ, Grad Sch Informat Sci, Hiroshima, Japan

来源：

TEXT, SPEECH, AND DIALOGUE (TSD 2015) | 2015年 / 9302卷

关键词：

Fashion item recommendation; Extracting characteristic; Text mining;

D O I：

10.1007/978-3-319-24033-6_6

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Many fashion magazines are available, and exclusive models in each magazine have a particular image. Readers of fashion magazines purchase fashion items by referencing the outfits worn by exclusive models. However, fashion recommendation systems for items based on the characteristics of an exclusive model do not exist on online shopping sites. Therefore, we propose an image extraction-based fashion recommendation system that considers information about the items worn by a model in a magazine. This study has performed an image extraction with a model based on this concept.

引用

页码：51 / 60

页数：10

共 50 条

[31] Extracting Relevant Terms from Mashup Descriptions for Service Recommendation
Yang Zhong
Yushun Fan
Tsinghua Science and Technology, 2017, 22 (03) : 293 - 302
[32] Group recommendation exploiting characteristics of user-item and collaborative rating of users
Kumar, Jitendra
Patra, Bidyut Kumar
Sahoo, Bibhudatta
Babu, Korra Sathya
MULTIMEDIA TOOLS AND APPLICATIONS, 2024, 83 (10) : 29289 - 29309
[33] Gender models: changing representations and intersecting roles in Dutch and Italian fashion magazines, 1982-2011
Kuipers, Giselinde
van der Laan, Elise
Arfini, Elisa A. G.
JOURNAL OF GENDER STUDIES, 2017, 26 (06) : 632 - 648
[34] Extracting Relations from Unstructured Text Sources for Music Recommendation
Sordo, Mohamed
Oramas, Sergio
Espinosa-Anke, Luis
NATURAL LANGUAGE PROCESSING AND INFORMATION SYSTEMS, NLDB 2015, 2015, 9103 : 369 - 382
[35] Extracting relevant terms from mashup descriptions for service recommendation
Zhong Y.
Fan Y.
Fan, Yushun (fanyus@tsinghua.edu.cn), 1600, Tsinghua University (22): : 293 - 302
[36] Group recommendation exploiting characteristics of user-item and collaborative rating of users
Jitendra Kumar
Bidyut Kumar Patra
Bibhudatta Sahoo
Korra Sathya Babu
Multimedia Tools and Applications, 2024, 83 : 29289 - 29309
[37] Collaborative filtering recommendation algorithm based on user interest characteristics and item category
Zhang, L. (zhangls@cqupt.edu.cn), 1600, Binary Information Press, P.O. Box 162, Bethel, CT 06801-0162, United States (09):
[38] Rating prediction for recommendation: Constructing user profiles and item characteristics using backpropagation
Purkaystha, Bishwajit
Datta, Tapos
Islam, Md Saiful
Marium-E-Jannat
APPLIED SOFT COMPUTING, 2019, 75 : 310 - 322
[39] Mining Latent Features from Reviews and Ratings for Item Recommendation
Zhai, Chenyu
Peng, Jing
2016 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE & COMPUTATIONAL INTELLIGENCE (CSCI), 2016, : 1119 - 1125
[40] Improving Pairwise Learning for Item Recommendation from Implicit Feedback
Rendle, Steffen
Freudenthaler, Christoph
WSDM'14: PROCEEDINGS OF THE 7TH ACM INTERNATIONAL CONFERENCE ON WEB SEARCH AND DATA MINING, 2014, : 273 - 282

← 1 2 3 4 5 →