activity
20172022
most citedStyle2Vec: Representation Learning for Fashion Items from Style Sets

29 citations · 50 across the 4 of their papers we have counts for

collaborators

6 papers

cs.IR202219 cited

Exploiting Session Information in BERT-based Session-aware Sequential Recommendation

Jinseok Seol, Youngrok Ko, Sang-goo Lee

In recommendation systems, utilizing the user interaction history as sequential information has resulted in great performance improvement. However, in many online services, user in…

cs.IR20221 cited

Technologies for AI-Driven Fashion Social Networking Service with E-Commerce

Jinseok Seol, Seongjae Kim, Sungchan Park +7

The rapid growth of the online fashion market brought demands for innovative fashion services and commerce platforms. With the recent success of deep learning, many applications em…

cs.IR20211 cited

False Negative Distillation and Contrastive Learning for Personalized Outfit Recommendation

Seongjae Kim, Jinseok Seol, Holim Lim +1

Personalized outfit recommendation has recently been in the spotlight with the rapid growth of the online fashion industry. However, recommending outfits has two significant challe…

cs.CV2021

Contrastive Learning for Unsupervised Image-to-Image Translation

Hanbit Lee, Jinseok Seol, Sang-goo Lee

Image-to-image translation aims to learn a mapping between different groups of visually distinguishable images. While recent methods have shown impressive ability to change even in…

cs.CV201729 cited

Style2Vec: Representation Learning for Fashion Items from Style Sets

Hanbit Lee, Jinseok Seol, Sang-goo Lee

With the rapid growth of online fashion market, demand for effective fashion recommendation systems has never been greater. In fashion recommendation, the ability to find items tha…

cs.CL2017

A Syllable-based Technique for Word Embeddings of Korean Words

Sanghyuk Choi, Taeuk Kim, Jinseok Seol +1

Word embedding has become a fundamental component to many NLP tasks such as named entity recognition and machine translation. However, popular models that learn such embeddings are…