Web-scale information extraction in knowitall: (preliminary results)
Proceedings of the 13th international conference on World Wide Web
Making mashups with marmite: towards end-user programming for the web
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
ManyEyes: a Site for Visualization at Internet Scale
IEEE Transactions on Visualization and Computer Graphics
What's in Wikipedia?: mapping topics and conflict using socially annotated category structure
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Attaching UI enhancements to websites with end users
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
An unobtrusive behavioral model of "gross national happiness"
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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Nowadays, a hitherto unseen amount of information can be found in the World Wide Web. While available, this information is fragmented among different web sites. This is especially true for implicit knowledge, not directly written in any one site, but arising from patterns and interactions between pages. For instance, the number of search results for a particular query string might be a meaningful indicator of its popularity or overall interest. Our research focuses on the design of an interface that allows end-users to access implicit information. A prototype application, Metabrain, embodies our solutions and makes it possible to mine the web for statistically relevant patterns, with the help of simple and straightforward algorithms and user interface. To help the users make sense of that information, Metabrain then allows custom visualizations to be crafted. User studies show that users can search for relevant information up to four times faster than using traditional Web search engines alone. A system usability scale questionnaire confirms the interface is usable and effective.