Abstract: Techniques for computing device update configuration are described. In implementations, an update service is employed to manage update groups for various types and/or classifications of computing devices. An update group can specify particular update statuses for functionalities of a computing device, such as device driver updates, software updates, firmware updates, and so forth. In at least some implementations, a computing device can be assigned to an update group based on attributes of the computing device, such as an identifier of a manufacturer for the computing device, a make identifier for the computing device, a model identifier, and so forth. Update information associated with the update group can be synchronized with the computing device.

Abstract: A computer-implemented method tracks diffusion. The method includes receiving a tracking request from an initiating user to track diffusion of content located at a content address. A computer tracking system generates a first shortened content address for the content address, from which the content is provided to the initiating user. The method includes receiving content requests from one or more requesting users, and generating, for each requesting user, a unique subsequent shortened content address for the content address. Content is provided to each requesting user using the subsequent shortened content address generated for each requesting user respectively. Each content request from the requesting users is made using either the first shortened content address or one of the subsequent shortened content addresses.

Abstract: A system and method for personalized search ranking may use a user's feedback to immediately reorder search results for this particular user so as to improve click-through rate. Upon receiving a query including one or more words, a search engine may identify a list of search results and display the search results on a search result page. A machine-learning module may collect information about a user's browsing activities on the result page, update estimates of relevance of the search results, and reorder the search result list to personalize it for the user.

Abstract: Example methods, apparatuses, and articles of manufacture are disclosed that may be used to provide or otherwise support contract auctions for sponsored search advertising for use in auction management systems.

Abstract: A system and method for personalized search ranking may use a user's feedback to immediately reorder search results for this particular user so as to improve click-through rate. Upon receiving a query including one or more words, a search engine may identify a list of search results and display the search results on a search result page. A machine-learning module may collect information about a user's browsing activities on the result page, update estimates of relevance of the search results, and reorder the search result list to personalize it for the user.

Abstract: A system comprises a machine readable storage medium having an index that, given a set of inputs, a set of outputs, a set of input categories, and a scoring rule, provides an ordered subset of the outputs for each input category. The outputs within each subset are ordered by predicted score with respect to an input from one of the input categories. At least one processor is capable of receiving an input corresponding to at least one of the set of input categories. The processor is configured for scoring a reduced set of outputs against the received input using the scoring rule. The reduced set of outputs includes a union of the subsets of outputs associated with each input category to which the received inputs correspond. The processor is configured for outputting a list including a subset of the reduced set of outputs having the highest scores.

Abstract: A system for providing a probability output and receiving an input includes a processor and a memory unit in communication with the processor. The memory has processor-executable instructions that configure the processor to provide a user interface having the probability output, wherein the probability output is in a graphical form and receives an input from the user via the user interface, wherein the user provides the input by marking portions of the graphical form of the probability output.