Abstract:
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.
Abstract:
Server systems are disclosed that receive content requests and respond with hardware-independent graphics commands instead of, or in addition to, unprocessed content items. The server systems can also generate text information regarding text in the requested content items, and provide the text information to user devices so that the user devices can have knowledge of the text in the content item. The user device can use the text information to handle user interactions with the content item, including copy, paste and search commands and other similar commands. Accordingly, the hardware-independent graphics commands-based representation may provide text interactivity and effects not otherwise available to content representations based on graphics commands or images of content.
Abstract:
Techniques and solutions for predicting web pages are described. Web page prediction can be performed using prediction models, including aggregate prediction models and user-based prediction models. Prediction models can be used to predict which web page (or which web pages) a user is likely to visit (e.g., to visit next after a current web page). Predicted web pages can be obtained in advance (e.g., pre-fetched and/or pre-rendered). Web page prediction can be performed by server computing environments and/or by client computing devices.
Abstract:
Server systems are disclosed that receive content request and respond with hardware-independent graphics commands instead of, or in addition to, unprocessed content items. Some server systems may act as intermediaries between user devices and content sources. The server systems can obtain content pages from content sources, process the content pages (e.g., using a headless browser), and provide hardware-independent graphics commands (e.g., vector graphics commands, that do not require specialized graphics hardware for execution) to user devices in response to requests for content. The hardware-independent graphics commands can be executed by client browsers to generate a representation of the content page that is the same or substantially the same as the representation that would have been generated by processing the content pages locally. A user device in receipt of such hardware-independent graphics commands can execute them without performing traditional content page processing, thereby improving user-perceived page load times.
Abstract:
Server systems are disclosed that receive content requests and respond with hardware-independent graphics commands instead of, or in addition to, unprocessed content items. The server systems can also generate text information regarding text in the requested content items, and provide the text information to user devices so that the user devices can have knowledge of the text in the content item. The user device can use the text information to handle user interactions with the content item, including copy, paste and search commands and other similar commands. Accordingly, the hardware-independent graphics commands-based representation may provide text interactivity and effects not otherwise available to content representations based on graphics commands or images of content.
Abstract:
Features are disclosed for determining which content item or items are likely to be requested by a particular user or device, or by a group of users or devices. The determined content items may be obtained independently of a request from the users or devices, and substantially current versions of the content items may be maintained at a server system, such as an intermediary system. Visual representations of the content items may be generated to reduce processing requirements at a user device. When the content items are determined to be likely to be requested by a particular user, a predicted time may also be determined, and the visual representations may be generated such that they are available at the predicted time.
Abstract:
A technology is described for operating a multi-tiered data processing service. An example method may include receiving a data rule set used to process data generated by a network addressable device included in a multi-tiered data processing service having computing nodes that are connected using one or more networks, where the computing nodes may have computing capacities to execute a portion of the data rule set using a rules engine. A computing node included in the multi-tiered processing service may be selected to host a portion of the data rule set on the computing node and a portion of the data rule set may be deployed to the computing node, where the data rule set may be registered with the rules engine that executes on the computing node and data generated by the network addressable device may be processed using the rules engine and the data rule set.
Abstract:
An intermediary system operates as an intermediary between content servers and user devices, and provides services for determining page authority based on user browsing behavior. One such service involves receiving user browsing behavior from at least one browser on a user device and using the browsing behavior to assign an authority ranking to a content page (e.g., web page). The intermediary system can determine the content page authority based on explicit user authority rankings and/or implicit authority indications in page traffic data.
Abstract:
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.
Abstract:
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.