From The Theme
PUBLISH ON DEMAND
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.
mediaX Research Project Update, Fall 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.