@inproceedings{b8e948bbccd24bdaa59917f330b6bfc8,
title = "Data-driven interactions for web design",
abstract = "This thesis describes how data-driven approaches to Web design problems can enable useful interactions for designers. It presents three machine learning applications which enable new interaction mechanisms for Web design: rapid retargeting between page designs, scalable design search, and generative probabilistic model induction to support design interactions cast as probabilistic inference. It also presents a scalable architecture for efficient data-mining on Web designs, which supports these three applications.",
keywords = "Machine learning, Web design",
author = "Ranjitha Kumar",
year = "2012",
doi = "10.1145/2380296.2380318",
language = "English (US)",
isbn = "9781450315821",
series = "Adjunct Proceedings of the 25th Annual ACM Symposium on User Interface Software and Technology, UIST'12",
pages = "51--54",
booktitle = "Adjunct Proceedings of the 25th Annual ACM Symposium on User Interface Software and Technology, UIST'12",
note = "25th Annual ACM Symposium on User Interface Software and Technology, UIST 2012 ; Conference date: 07-10-2012 Through 10-10-2012",
}