Amazon Technologies, Inc.

Amber Kathleen Joehnk

Leo Parker Dirac

Waqas Syed Ahmed

Kevin Michael Small

Aditya Rekha Dharanipragada

Guy Levanon

Simon Hachey

Hannes Scheidler

Technologies for determining, displaying, and leveraging reasons to buy for categories of items. Aspects (reasons to buy) may be predetermined for categories of items from a corpus of item information. For each item in a category, community-sourced content (e.g., customer reviews) may be identified for (aligned to) each aspect, and relevant comments may be extracted from the content. The comments may be analyzed, for example according to sentiment, to provide scoring and summary statistics for the aspects. Items may be ranked according to the summary statistics. The aspects for an item may be displayed, with extracted comments and/or summary statistics provided for each aspect. Items in a category or across categories may be compared according to the aspects. Aspects may be used in searches for items within categories to filter the items according to one or more of the aspects.

Determining item feature information from user content

Growing community of inventors

Seattle, WA, United States of America

Amber Kathleen Joehnk