Amazon Technologies, Inc.

Gregory Nicholas Hullender

Joseph Spencer King

Nikunj Aggarwal

Robert Wayne Roth

Manigandan Natarajan

Wainwright Gregory Siady Yu

Ramya Dass

Brandon LaBranche Watson

Sridhar Sampath

Joon Hao Chuah

James Joseph Poulin

Santosh Kumar Asokan

Christopher Andrew Stephens

Erik Warren Selberg

Mohammad A Kanso

Mohammed Kanso

Wainwright Gregory Yu

Brandon Labranche Watson

Techniques are provided for selectively and dynamically determining one or more words of an electronic book to present with comprehension guides. For instance, an electronic device rendering an electronic book may determine whether to display some, all, or no words of the book with comprehension guides for words within the electronic book based on word difficulty, contextual importance or aspects of the user. Techniques are also provided for determining the content of comprehension guides to be presented with the words.

Selective display of comprehension guides

Embodiments of systems and methods can determine evaluations of the quality of task results provided by judges. Certain embodiments can determine the quality evaluations with relatively little overlap of judges (e.g., two or three judges). The quality evaluations may include determining an error rate or a confidence index for a judge or for a particular judgment made by the judge. Certain embodiments may determine the quality evaluations by intercomparing judging results from multiple judges without requiring human intervention, comparison to evaluation data known (or assumed) to be accurate, or input from an external judge review panel. In some implementations, task results can be combined with a confidence score (based at least in part on the quality evaluation of the judge who provided the task result), and this information can be used as training data to improve performance of machine learning algorithms.

Evaluation of task judging results

Disclosed are various embodiments for using contributor-provided attributes in conjunction with an electronic item catalog. A computer reconciles a plurality of attributes for an item in an electronic catalog using feedback data related to the item. Each of the attributes is provided by one of a plurality of merchants. The reconciled attribute of the item is updated in the electronic catalog.

Using feedback to reconcile catalog item attributes

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Seattle, WA, United States of America

Gregory Nicholas Hullender