Amazon Technologies, Inc.

Llewllyn J Mason

Andrew Bruce Dickinson

Tom Killalea

Richard Jeffrey Cole

Francis J Kane, Jr

Brian James Schuster

Daniel Bruce Lloyd

Samuel A Minter

Michal Maciej Bryc

Mark Jacobson

Raj K Kizhakkekalathil

Karen R Haberkorn

Mike Perkowitz

User content access events pertaining to a content item, such as an ebook, audio, video file, and so on, are collected and analyzed to determine progress data, including abandonment information about when the content item, or a portion thereof, has been abandoned. Once determined, recommendations may be presented based on the progress data from similar users.

Recommendations based on progress data

Techniques for automated targeting of content components to users are described. Content components are selected and exposed through renderable pages for viewing by a population of users. User activity following exposure is tracked in an effort to identify which types of users (as characterized by certain attributes) are likely to act on the content components. The users are segmented into groups according to the attributes and the segments are fed back to aid in selection of content components to be exposed to the users. This enables more granular targeting of the content components to those users who exhibit the attributes that define the specific groups.

Automated targeting of content components

An ad system is described for providing ad selections in response to an ad presentation opportunity. The ad system can use multiple content providers to generate multiple sets of ad candidates. The content providers can apply different ad selection paradigms in generating their sets of ad candidates. The paradigms may act on different aspects of a context pertaining to the ad presentation opportunity. A chooser module and filtering module can cull the set of ad selections from among the plural sets of ad candidates. At least one content provider uses machine learning functionality in generating ad candidates, such as a Na&#xef;ve Bayesian approach, an affiliate similarity approach, etc. Various content providers also find application in a stand-alone mode.

Providing ad information using plural content providers

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Seattle, WA, United States of America

Llewllyn J Mason