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The Web has become a large repository of information with varying qualities. Many users often consume information without knowing its quality. Although automatic methods can be used to obtain measurements of certain aspects of quality, they are not reliable and cannot measure all aspects of quality. Users can detect errors and reliably assess aspects of quality that cannot be measured by automatic methods. However, there is a lack of technology support for users to record and share their feedback. This paper aims to develop technologies to allow users to collaboratively assess information quality on the Web. The solution combines the capabilities of machines and humans to obtain comprehensive, reliable, and scalable measurements of information quality.
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