Amazon Technologies, Inc.

Kyle Robert Stanley

Martin C Eitreim

Ronald G Siemens

Sachin Birendra Singh

Yu Liu

Shyam S Sundaramurthy

Jiahu Deng

Embodiments of a system and method for evaluating correction submissions with supporting evidence may include, subsequent to a submitter being provided with item description information for an item offered for sale, receiving a correction submission specified by the submitter. The correction submission may specify a proposed modification to an attribute(s) in the item description information. Embodiments may include generating a measure of risk associated with performing the proposed modification to the item description information. Embodiments may also include, based on an evaluation of the measure of risk and one or more risk criteria, generating an indication that specifies whether the proposed modification to the item description information is permitted to be performed. Embodiments may also include receiving information for confirming the validity of the correction submission, which may include an image (e.g., a product image), or a network address (e.g., a URL to manufacturers website), or other information described herein.

System and method for evaluating correction submissions with supporting evidence

Systems and methods for generating a score for use in automated processing of correction submissions are presented. In one embodiment, a submission value from a correction submission obtained from a submitter is obtained. The submission value corresponds to a proposed correction of an attribute of an item, the item having a plurality of attributes that describe the item, and the submission value corresponds to one of the plurality of attributes of the item. The current attribute value of the item that corresponds to the submission value is obtained. A first set of characterization values is generated for the submission value according to a first set of criteria. A second set of characterization values for the current attribute value is generated according to a second set of criteria. Using the first and second sets of characterization values, a score is generated for the correction submission. The score is stored in a data store in association with the correction submission.

Automated acceptance or rejection of consumer correction submissions

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Seattle, WA, United States of America

Kyle Robert Stanley