Amazon Technologies, Inc.

Ameet Nirmal Vaswani

Brett Richard Taylor

Peter F Hill

Sajeeva Lakmal Bandara Pallemulle

Ranganath Atreya

Saral Jain

Samuel John Young

Ivan King Yu Sham

Matthew Lloyd Trahan

Patrick Joseph Armstrong

Aakarsh Nair

David Andrew Killian

Faizal S Kassamali

Ryan Crawford Tucker

Michael V Zampani

Arun Sundaram

Muneer Mirza

Steven Michael Reddie

Andrew Hayden

Justin Jon Derby

Leonardo Davi Viccari

Camilla De Oliveira Penna Tavares

Rohit Krishna Kumar

Andrew James Guenther

Vincent Roseberry

Ian William Stewart

Scott Zachary Bressler

Li Yan

Yousef Zachary Khwaja

Peter Frank Hill

Eric Jason Brandwine

Aaron Brown

Peter Sven Vosshall

Venkates Paramasivam Balakrishnan

Alexander Clark Prater

Eric Wayne Schultze

Natalie Thuy-Tien Nguyen

Christopher Thomas

Dhruva Lakshmana Rao Batni

Kurt Kufeld

Sandesh Doddameti

Preetha Chatterjee

Paul Lee Coleman, Iv

Nikhil Dinkar Joshi

Nan Zhong

Gopal Harikumar

Kamlesh Nanda

Vikas Mehta

Ming-Hsiu Wang

Bryan Kenneth Summersett

Ekechi Karl Edozie Nwokah

Erik Ackermann

Yoong Han Chew

Gregory Martin

Joseph Papa

Ivan King Sham

Metthew Lloyd Trahan

Generally described, one or more aspects of the present application correspond to a content rendering system. A content management service hosts content on behalf of the content provider. The content management service includes one or more rendering engines that receive content from the one or more content providers that are registered with the content management service. Each content rendering engine can be configured to receive a content resource and generate at least one piece of processed content that can be rendered on a user device.

Network-based content rendering

This disclosure describes techniques for utilizing sensor data to automatically determine the results of events within a system. Upon receiving sensor data indicative of an event, the techniques may analyze the sensor data to determine a result of the event, such as that a particular user associated with a user identifier selected a particular item associated with an item identifier. The techniques described herein may determine when sensor data is to be stored for a default amount of time, and when sensor data is to be stored for a greater amount of time. By retaining data in an intelligent manner, the system is able to function accurately without unduly taxing storage constraints.

Automated sensor data retention

Features are disclosed for selecting preferred content request modes on a client computing device when initiating content requests. The request modes may correspond to direct requests (e.g., requests made from a client device directly to a content sever hosting requested content) or to indirect requests (e.g., requests made from the client device to the content server via an intermediary system). The preferred request modes made be based on a statistical analysis of performance data (e.g., prior content load times) observed or recorded by the client computing device in connection with prior content requests. Randomly selected request modes may be used to provide additional data for performance analysis.

Browser-based analysis of content request mode performance

Features are disclosed for analyzing requests for network accessible content, including but not limited to web pages, to determine which topics and other characteristics are popular or are gaining in popularity ('trending'). Content items or sources may be profiled to determine characteristics that two or more content items or sources may have in common. Content requests from multiple client devices may be tracked and analyzed to determine the trending or popular characteristics. Data feeds or reports regarding the summarized content requests may be generated and distributed to content servers and other entities. The data feeds may be used to tailor content, such as by highlighting or featuring content associated with the most-requested content characteristics, or utilizing demographic data to tailor content for different users.

Determining popular and trending content characteristics

Techniques and solutions are described for content synchronization across devices. A web page currently being viewed at a first device associated with a user profile of a user can be identified. Browsing information for the page (such as URL, scrolling location, and a DOM element) may be stored in the profile. The DOM element may be associated with page content displayed during a browsing session in a viewport while the web page is at the current scrolling location. The browsing information may be updated dynamically, upon detecting a change in the current scrolling location of the page at the first device. A request for displaying the web page at a second device associated with the user profile may be received. The browsing information for the web page may be provided to the second device, so that the web page with the current scrolling location is displayed at the second device.

Content synchronization across devices

Network accessible content, including but not limited to web pages, can be analyzed to identify characteristics of the content. Historical content requests associated with users and/or other user-specific information can be analyzed to identify user interests. Content can then be provided or recommended to users based on content characteristics and user interests. The content that is provided or recommended may be trending content that has at least a threshold level of popularity, became popular recently, and/or is associated with a threshold level of social network activity.

Identification of trending content using social network activity and user interests

A system is disclosed that enables a user to access a first piece of content on a first computing device while accessing a related, but different piece of content on a second computing device. In some cases, the different piece of content is a portion of the first piece of content. In some embodiments, the system can automatically identify complementary content and can automatically cause the second computing device to access the complementary content without the user interacting with the second computing device. In some cases, the system may reformat the complementary content for presentation to the user based on characteristics of the second computing device.

System for providing multi-device access to complementary content

Features are disclosed for generating request decision models for use by client computing devices to determine request paths or modes for content requests. The request modes may correspond to direct requests (e.g., requests made from a client device directly to a content server hosting requested content) or to indirect requests (e.g., requests made from the client device to the content server via an intermediary system). The request decision models may be trained by a machine learning algorithm using performance data (e.g., prior content load times), contextual information (e.g., state information associated with devices at times content requests are executed), and the like.

Browser-based selection of content request modes

Features are disclosed for determining preferred content request modes for client computing devices when initiating content requests. The request modes may correspond to direct requests (e.g., requests made from a client device directly to a content sever hosting requested content) or to indirect requests (e.g., requests made from the client device to the content server via an intermediary system). The preferred request modes made be based on a statistical analysis of performance data (e.g., prior content load times) obtained from one or more client computing devices for a given content item, group of content items (e.g., domain), and the like.

Performance-based determination of request modes

A system and process are disclosed for providing users with page previews during page loading events, such that the delay experienced before the display of page content is reduced. The previews may include screenshots of the pages or of portions thereof, and may be generated periodically and cached by the system for delivery to user devices. The process of generating and delivering the previews via the Internet or some other network may be implemented partly or wholly within an intermediary system that sits logically between the user devices and content servers. The process may be used with existing browsers without the need for any browser modifications, or may be used with a 'preview-aware' browser that includes special program code for providing page previews.

Delivery and display of page previews during page retrieval events

A user device that presents a static non-interactive graphical representation of a content page received from an intermediary system may emulate controls or interactive elements included in the content page based on control metadata received from the intermediary system. The emulated controls enable the user device to restore the interactivity that is lost by generating the graphical representation of the content page. Further, the emulated controls may be included as part of an overlay layer positioned above the graphical representation of the content page. Information or control metadata for each control included in the content page may be provided to the user device with the graphical representation of the content page. The user device may use the control metadata to identify types of controls to emulate and where to position the emulated control with respect to the graphical representation of the content page.

Emulation of control resources for use with converted content pages

Features are disclosed for generating bundles of content items and proactively providing the bundles to client devices. The bundles may be provided to client devices in response to requests for the content page that references the content items in the bundle, or in response to a request for a content page hosted by the same domain as the content items in the bundle. A browser module executing on the client device can extract the referenced content items in the bundle and cache them in a local content cache at the client device prior to the client device receiving and processing a requested content page. As a result, the browser module may have access to cached versions of referenced content items when processing the requested content page even if the referenced content items were not present when the requested content page was requested.

Architecture for proactively providing bundled content items to client devices

Features are disclosed for analyzing requests for network accessible content, including but not limited to web pages, to determine which topics and other characteristics are popular or are gaining in popularity ('trending'). Content items or sources may be profiled to determine characteristics that two or more content items or sources may have in common. Content requests from multiple client devices may be tracked and analyzed to determine the trending or popular characteristics. Data feeds or reports regarding the summarized content requests may be generated and distributed to content servers, advertisers, and other entities. The data feeds may be used to tailor content, such as by highlighting or featuring content associated with the most-requested content characteristics, or utilizing demographic data to tailor content for different users.

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Seattle, WA, United States of America

Ameet Nirmal Vaswani