Abstract: Embodiments seek to improve prefetch hinting using time-dependent, machine-generated hints. Some embodiments operate in context of client machines in communication hinting machines that can develop information about whether and how resources are used in network transactions over time by collecting “resource samples.” Each resource sample can identify rendering status information of a resource at a sample time. The time-based samples can be used to compute time-based probabilities for the resources, indicating, for example, the likelihood of a resource being used to render a web page at some subsequent time. Time-dependent hints can be generated as a function of the time-based probabilities, and the time-dependent hints can be used to improve prefetching by optimizing the hinting information with respect to a particular request time (e.g., the prefetching hints for rendering a web page can be generated in a manner that accounts for when the web page is being rendered).

Abstract: Embodiments seek to improve prefetch hinting using time-dependent, machine-generated hints. Some embodiments operate in context of client machines in communication hinting machines that can develop information about whether and how resources are used in network transactions over time by collecting “resource samples.” Each resource sample can identify rendering status information of a resource at a sample time. The time-based samples can be used to compute time-based probabilities for the resources, indicating, for example, the likelihood of a resource being used to render a web page at some subsequent time. Time-dependent hints can be generated as a function of the time-based probabilities, and the time-dependent hints can be used to improve prefetching by optimizing the hinting information with respect to a particular request time (e.g., the prefetching hints for rendering a web page can be generated in a manner that accounts for when the web page is being rendered).

Abstract: Systems, computer-readable media, methods, and apparatuses for interactive tools for dynamic evaluation of online content are described. One example method includes receiving, by a client device, a selection of first content from a first content provider, the first content obtained using a first uniform resource identifier (“URI”); in response to receiving, by the client device, a request to access evaluation information associated with the first URI, transmitting a request to access the evaluation information to a second content provider using a second URI; receiving, by the client device from the second content provider, second content associated with the first URI, the second content having the evaluation information; generating, by the client device, annotations for the first content using the evaluation information; and displaying the first content and the annotations, the annotations displayed within the first content.

Abstract: Systems, computer-readable media, methods, and apparatuses for interactive tools for dynamic evaluation of online content are described. One example method includes receiving, by a client device, a selection of first content from a first content provider, the first content obtained using a first uniform resource identifier (“URI”); in response to receiving, by the client device, a request to access evaluation information associated with the first URI, transmitting a request to access the evaluation information to a second content provider using a second URI; receiving, by the client device from the second content provider, second content associated with the first URI, the second content having the evaluation information; generating, by the client device, annotations for the first content using the evaluation information; and displaying the first content and the annotations, the annotations displayed within the first content.