Determining item feature information from user content

US10410224B1 · kind B1 · utility

Assignee

• AMAZON TECHNOLOGIES, INC. · US

Inventors

• Guy Levanon · Seattle, US
• Waqas Ahmed · Bellevue, US
• Leo Parker Dirac · Seattle, US
• Aditya Rekha Dharanipragada · Seattle, US
• Simon Hachey · Seattle, US
• Amber Kathleen Joehnk · Seattle, US
• Hannes Scheidler · Mercer Island, US
• Kevin Michael Small · Seattle, US

Key dates

• Filing date: Jun 12, 2014
• Grant date: Sep 10, 2019
• Expiry date: Apr 5, 2037

Classification

• Technology area (CPC G): Physics
• CPC primary: G06Q30/02
• WIPO field: IT methods for management
• WIPO sector: Electrical engineering

Abstract

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.