I wonder if someone in trouble in the Cyberia suit could be made to look like they’re in trouble, in ways richer than a flash LED.
Has anyone tried to predict information scent?
Google Scholar: measuring information scent
The Scent of a Site: A System for Analyzing and Predicting Information Scent, Usage, and Usability of a Web Site, 3333 Coyote Hill. You know what time it is.
Designers and researchers of users’ interactions with the World Wide Web need tools that permit the rapid exploration of hypotheses about complex interactions of user goals, user behaviors, and Web site designs
True and possibly more true in the wearable world.
Web data-mining technique
What does information foraging theory have to do with data mining? This is a question for another day.
Given the magnitude of user interaction data,
Is this going to be a solution that relies on web analytics, data captured after the design is created? Ideally, this wouldn’t be the case. At design-time, prediction.
the ultimate goal is to evolve the system so that it can be effectively employed by practicing Website designers and content providers.
Needed. but let’s keep going and see what we’re talking about.
WebCriteria SiteProfile uses a browsing agent to navigate a Web site using a modified GOMS model and record download times and other information.
That’s interesting.
Current approaches to Web site analysis are aimed at the Webmasters who are interested in exploring questions about the current design of a Web site and the current set of users. However, Webmasters must also be interestedin predicting the usability of alternative designs of their Web sites. They also seek to answer these same questions for new kinds of (hypothetical) users who have slightly different interests than the current users.
🤚🏻 HI.
longest repeated subsequence (LRS,) to extract the surfing patterns of users foraging
I think this means your taking web metrics, each visits as a path through a graph. And you’re finding where nodes often “compete” with each other. So 2 paths with a lot of overlap, possibly complete overlap upto a point, a fork in the road, and the point of divergence is the point of competition. maybe this signals user’s needs? At least it signals two places one of which needs more scent to ease competition.. maybe?
a novel way of capturing user information goals, the affordances of Web sites,
I think we’re measuring both: Goals of the agent and the affordances of the environment.
These techniques are based on psychological models [6], which are closely related to standard information retrieval techniques, and Web data mining techniques based on the analysis of Content, Usage, and hyperlink Topology(CUT
I’m completely unfamiliar with CUT. These are “related”? I have questions.
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