Amazon Technologies, Inc.

Jeffrey L Belle

Tom Killalea

Michael Anthony Frazzini

Janna Hamaker

Vikram Sathyanarayana Anbazhagan

Patrick Ludvig Bajari

Daniel Leng

Jeffrey Paul Helbling

Kelly Paulson

Mary Ellen Fullhart

Victoria A Griffith

Ana Maria Mocanu

Based on historical data describing product sales or other types of transactions, indicator scores may be calculated for users who have purchased, reviewed, or otherwise consumed products, the indicator scores based on subsequent diffusion of the products. Measured, current activities of the scored users with regard to another product may then be employed to develop a diffusion model that predicts the future sales of the other product over time. The diffusion model may be employed to determine product pricing, marketing, distribution, or acquisition.

Diffusion prediction based on indicator scoring

Techniques for use with an electronic book reader include receiving localized evaluative feedback from users, pertaining to different locations within electronic content. The localized feedback is collected at a server and reported to content creators in reports that are formatted to indicate characteristics of the feedback at different locations within the electronic content.

Localized feedback for content creation

A system and method of data mining for republishing is described. In some embodiments products having a high potential for increased sales through republishing are identified based on relationships with products having consistent sales. In some embodiments products having a high potential for increased sales through republishing are identified based on sales in one language and availability of rights in another language. In one aspect, translations are facilitated via a translations marketplace.

Data mining for targeted republishing

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Seattle, WA, United States of America

Jeffrey L Belle