Using Thumbnails to Search the Web and Browse Documents
Speaker: Ruth Rosenholtz , MIT BCS
Date: December 5 2003
Text summaries contain a great deal of valuable information about a document (e.g. the URL, title, size, and sentences that summarize the document or contain search keywords). On the other hand, text summaries do not provide much information about page layout, genre (is this someone's homepage? a company website?), or about images on the page. Furthermore, reading a text summary can be slow and tedious.
On the other hand, documents are sometimes represented by a thumbnail -- a reduced-size image of the document. The advantages and disadvantages of this "plain thumbnail" representation are largely complementary to those of a text summary. In this talk, I'll introduce a technique for creating what we call "enhanced thumbnails" of web pages, which combine the advantages of image thumbnails and text summaries to improve Web search. The design of these thumbnails is based on knowledge of human vision, particularly of visual attention.
In addition to aiding search through a large number of documents, enhanced thumbnails can help when you have found the document you are looking for, and need to find information within that document. To demonstrate this, we have created a new Web browser, called "PopoutPrism," which is based on enhanced thumbnails. In the 2nd half of this talk I'll give a demo of PopoutPrism, and discuss issues and perceptually based principles in its design.
This is work done in collaboration with Allison Woodruff, summer interns Andrew Faulring and Bongwon Suh, and post-doc Julie Morrison.
Ruth Rosenholtz is a Principal Research Scientist in the Department of Brain and Cognitive Sciences, having just joined MIT this semester after 7 years at the Palo Alto Research Center (formerly Xerox PARC). Ruth's background is in electrical engineering, particularly computer vision. More recently, however, she has studied human vision, and in particular visual search and attention. Her engineering background shows through in her focus on finding predictive mathematical models of phenomena in human vision, and in her interest in applying knowledge of human perception to the design of better user interfaces and information visualizations. Ruth's current obsession is understanding and recognizing clutter.
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