Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Tak Yeon Lee"'
Autor:
Tak Yeon Lee, Benjamin B. Bederson
Publikováno v:
PeerJ Computer Science, Vol 2, p e91 (2016)
End-user programming (EUP) is a common approach for helping ordinary people create small programs for their professional or daily tasks. Since end-users may not have programming skills or strong motivation for learning them, tools should provide what
Externí odkaz:
https://doaj.org/article/3b6527d04b3f40f6b12896a719b44dc1
Autor:
Camille Harris, Ryan Rossi, Sana Malik, Jane Hoffswell, Fan Du, Tak Yeon Lee, Eunyee Koh, Handong Zhao
Publikováno v:
Companion Proceedings of the ACM Web Conference 2023.
Autor:
Phoebe Moh, Sana Malik, Fan Du, Leilani Battle, Eunyee Koh, Tak Yeon Lee, Jane Hoffswell, Zehua Zeng
Publikováno v:
IEEE Transactions on Visualization and Computer Graphics. 28:346-356
Although we have seen a proliferation of algorithms for recommending visualizations, these algorithms are rarely compared with one another, making it difficult to ascertain which algorithm is best for a given visual analysis scenario. Though several
Autor:
Tak Yeon Lee, Casey Dugan, Werner Geyer, Tristan Ratchford, Jamie Rasmussen, N. Sadat Shami, Stela Lupushor
Publikováno v:
Proceedings of the International AAAI Conference on Web and Social Media. 7:341-350
This paper examines the relationship between motivational design and its longitudinal effects on crowdsourcing systems. In the context of a company internal web site that crowdsources the identification of Twitter accounts owned by company employees,
Publikováno v:
CHI Conference on Human Factors in Computing Systems Extended Abstracts.
Autor:
Ryan A. Rossi, Handong Zhao, Sungchul Kim, Tak Yeon Lee, S. Muthukrishnan, Zuohui Fu, Yikun Xian, Gerard de Melo
Publikováno v:
KDD
Column annotation, the process of annotating tabular columns with labels, plays a fundamental role in digital marketing data governance. It has a direct impact on how customers manage their data and facilitates compliance with regulations, restrictio
Autor:
Joel Chan, Fan Du, Sungchul Kim, Xin Qian, Sana Malik, Ryan A. Rossi, Eunyee Koh, Tak Yeon Lee
Publikováno v:
KDD
Visualization recommendation is important for exploratory analysis and making sense of the data quickly by automatically recommending relevant visualizations to the user. In this work, we propose the first end-to-end ML-based visualization recommenda
Autor:
Sungchul Kim, Ryan A. Rossi, Joel Chan, Xin Qian, Sana Malik, Fan Du, Eunyee Koh, Tak Yeon Lee
Publikováno v:
WWW
Scientific-style figures are commonly used on the web to present numerical information. Captions that tell accurate figure information and sound natural would significantly improve figure accessibility. In this paper, we present promising results on
Autor:
Xin Qian, Ryan A. Rossi, Fan Du, Sungchul Kim, Eunyee Koh, Sana Malik, Tak Yeon Lee, Nesreen K. Ahmed
Visualization recommendation work has focused solely on scoring visualizations based on the underlying dataset and not the actual user and their past visualization feedback. These systems recommend the same visualizations for every user, despite that
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::286239cefb30cd21c6870bec15570466
http://arxiv.org/abs/2102.06343
http://arxiv.org/abs/2102.06343
Autor:
XIN QIAN, ROSSI, RYAN A., FAN DU, SUNGCHUL KIM, EUNYEE KOH, MALIK, SANA, TAK YEON LEE, AHMED, NESREEN K.
Publikováno v:
ACM Transactions on the Web; Sep2022, Vol. 16 Issue 3, p1-47, 47p