Popular websites Wikipedia and Tripadvisor rely on public participation to build up their pool of information, in a process known as crowd data sourcing.
Even though this kind of collective intelligence may be valuable, filtering inaccuracies and offensive material out of these sites is evidently a costly undertaking.
Now Tova Milo, professor at Tel Aviv University's Blavatnik School of Computer Science, has developed a new technology that can automatically evaluate such data.
It can perform tasks like checking online encyclopaedia content and alerting moderators about potentially offensive commentary -- both saving valuable man-hours and improving the quality of information, according to a Tel Aviv statement.
Bookselling site Amazon also uses such data to provide reviews and book lists, and most news sites crowd-source comments and responses to articles.
Because these sites are designed to be dynamic, Milo explains: "Every day, old information is updated and new information comes in. It's very difficult to maintain."
Typically, overworked staff members are tasked with sorting through the piles of information received to determine if any inappropriate material has made its way onto a site.
But Milo's database technology can change that as well. Ultimately, the system ensures that the crowd is being used efficiently.
"It's about knowing to ask the right people the right questions," says Milo. By using human input more selectively, the results will be of a higher quality, and sites will save money and time on controlling content.
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