Design mining the web

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Abstract/Contents

Abstract
The billions of pages on the Web today provide an opportunity to understand design practice on a massive scale. Each page comprises a concrete example of visual problem solving, creativity, and aesthetics. In recent years, data mining and knowledge discovery have revolutionized the Web, driving search engines, advertising platforms, and recommender systems that are used by more than two billion people every day. However, traditional data mining techniques tend to focus on the content of Web pages, ignoring how that content is presented. What could we learn from mining design? This thesis introduces design mining for the Web, and presents a scalable software platform for Web design mining called Webzeitgeist. Webzeitgeist consists of a repository of pages processed into data structures that facilitate large-scale design knowledge extraction. With Webzeitgeist, users can find, understand, and leverage visual design data in Web applications. In this dissertation, I demonstrate how software tools built on top of Webzeitgeist can be used to dynamically curate design galleries, search for design alternatives, retarget content between page designs, and even predict the semantic role of page elements from design data. As more and more creative work is done digitally and shared in the cloud, Webzeitgeist illustrates how design mining principles can be applied to benefit content creators and consumers.

Description

Type of resource text
Form electronic; electronic resource; remote
Extent 1 online resource.
Publication date 2013
Issuance monographic
Language English

Creators/Contributors

Associated with Kumar, Ranjitha Sampath
Associated with Stanford University, Department of Computer Science.
Primary advisor Klemmer, Scott
Thesis advisor Klemmer, Scott
Thesis advisor Hanrahan, P. M. (Patrick Matthew)
Thesis advisor Winograd, Terry
Advisor Hanrahan, P. M. (Patrick Matthew)
Advisor Winograd, Terry

Subjects

Genre Theses

Bibliographic information

Statement of responsibility Ranjitha Sampath Kumar.
Note Submitted to the Department of Computer Science.
Thesis Ph.D. Stanford University 2013
Location electronic resource

Access conditions

Copyright
© 2013 by Ranjitha Sampath Kumar
License
This work is licensed under a Creative Commons Attribution 3.0 Unported license (CC BY).

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