Amazon Technologies, Inc.

Arijit Ghosh

Christopher Vander Mey

Brian David Marsh

Nikolas Clemens Gloy

Techniques are described for managing content by identifying content that has attributes of interest (e.g., content that is useful, humorous and/or that otherwise has a sufficiently high degree of quality) and by determining how to use such identified content. In some situations, a piece of content is automatically assessed in a manner based on automatically assessed levels of trust in users who are associated with the content, such as a user who authored or otherwise supplied the content and/or users who evaluated the content. For example, an automatically assessed level of trust for a user may be based on prior activities of the user and be used to predict future behavior of the user as a supplier of acceptable content and/or as an acceptable evaluator of supplied content, such as based on prior activities of the user that are not related to supplying and/or evaluating content.

Assessing content based on assessed trust in users

Techniques are described for enhancing the reliability of information received from users in various ways, such as by analyzing votes or other ratings supplied by a user in order to identify fraudulent and other unreliable ratings. Such analysis may be based at least in part on prior ratings submitted by the user, such as based on one or more patterns indicating that the user has a bias for or against one or more of various aspects. Unreliable ratings can then be excluded from use in various ways. This abstract is provided to comply with the rules requiring it, and is submitted with the intention that it not limit the scope of the claims.

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Mercer Island, WA, United States of America

Arijit Ghosh