Acquiring Reliable Ratings from the Crowd
نویسندگان
چکیده
We address the problem of acquiring reliable ratings of items such as restaurants or movies from the crowd. We propose a crowdsourcing platform that takes into consideration the workers’ skills with respect to the items being rated and assigns workers the best items to rate. Our platform focuses on acquiring ratings from skilled workers and for items that only have a few ratings. We evaluate the effectiveness of our system using a realworld dataset about restaurants.
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تاریخ انتشار 2015