Researchers at Case Western Reserve University said that anonymous testers recruited through crowdsourcing preferred the new search tool nearly two-to-one over a keyword-based lookup interface and the most commonly available lookup search interface using Google.
Side-by-side comparisons showed the scientists' Conjunctive Exploratory Navigation Interface (CENI), which combines two search modes and a more comprehensive way to organise and tag data, is more effective than looking up items by matched keywords alone.
In one test, for example, a keyword search came up with 89 responses to a question: "What are the typical vision problems associated with diabetes?" CENI came up with the most applicable 13 by selecting appropriate menus, they said.
"Most people have an iPhone or laptop that stores a wide variety of information and, often, you can't find it when you need it, even though you know it's there," said GQ Zhang, professor of electrical engineering and computer science, division chief of Medical Informatics at Case Western Reserve and an author of the study.
CENI overcomes this limitation by allowing data to be tagged into as many areas as relevant, and provides an interface and system that leverages multiple tags for each single data item.
Researchers have a working prototype designed specifically for the health resource website, NetWellness.
The not-for-profit site allows the public to ask health professionals at Case Western Reserve, Ohio State University and the University of Cincinnati health-related questions.
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