From The Theme
PUBLISH ON DEMAND

WHAT IF
What if there were a machine learning algorithm that could identify and label design elements of web pages?

WHAT WE SET OUT TO DO
We focused on one popular class of semantic identifiers – those concerned with the structure (information architecture) of a page. Across webpages, there is no consistency of data, which raises the questions of how to build a system that can deal with unruly data. We explored various tactics for adding structural semantics to webpages.

WHAT WE FOUND
Using a crowd-sourced approach, recruiting 400 participants to gather data for us, we developed a new kind of supervised design-based machine learning algorithm that can streamline structured visual descriptors for page elements from a central repository, the Webzeitgeist platform. Our results help users understand design demographics, automate design curation, and support new data-driven interactions.

LEARN MORE
mediaX Research Project Update, Fall 2013

mediaX Research Theme Update, Spring 2013

PEOPLE BEHIND THE PROJECT
Scott Klemmer is an Associate Professor of Cognitive Science and Computer Science & Engineering at UC San Diego, where he is a co-founder and co-director of the Design Lab. He previously served as Associate Professor of Computer Science at Stanford, where he co-directed the HCI Group, held the Bredt Faculty Scholar chair, and was a founding participant in the d.school. His group’s research tools harvest and synthesize examples to empower more people to design, program, learn, and create.

Maxine Lim is the Co-founder and Chief Product Officer at Apropose, Inc. She holds a BS in Computer Science from Stanford University, where she worked and published as a researcher in the Computer Science Department and in the Stanford School of Medicine.