Abstract: A content provider can provide content, such as advertisements or other promotional material, for display by a mobile application. As contextual information is typically limited for mobile applications, the content provider can use other information in addition to or in place of contextual information to select advertisements. This information can include location information, user activity with regards to the mobile application, information regarding a recipient of the advertisement, such as demographic information, information regarding the mobile application, such as information regarding the type of mobile application, and product inventory information. A user profile also may be used to select advertisements. The user profile can include a set of merchants and merchant types, for example clothing retailers, to which a user may be more responsive. The user profiles can be generated and updated by logging merchants that the user visits or interacts with via advertisements.

Abstract: A content provider can provide content, such as advertisements or other promotional material, for display by a mobile application. As contextual information is typically limited for mobile applications, the content provider can use other information in addition to or in place of contextual information to select advertisements. This information can include location information, user activity with regards to the mobile application, information regarding a recipient of the advertisement, such as demographic information, information regarding the mobile application, such as information regarding the type of mobile application, and product inventory information. A user profile also may be used to select advertisements. The user profile can include a set of merchants and merchant types, for example clothing retailers, to which a user may be more responsive. The user profiles can be generated and updated by logging merchants that the user visits or interacts with via advertisements.

Abstract: A bid for a content slot from a content provider is received. The bid includes a revenue-sharing bid. It is determined that the bid is a winning bid and content is presented from the content provider in the content slot. Presentation details are logged that include a time when the content was presented. At a later time, an indication is received of an action, the indication including an indication that the action is responsive to the content having been presented previously. Based on the action, the content provider is charged an appropriate amount based on the revenue sharing bid.

Abstract: Methods, systems, and computer program products are provided for detecting trigger events and providing information in response to trigger events. One example method includes identifying, from a network presence of an individual, historical data associated with the individual including determining data that is relevant to an activity, identifying, from the network presence of the individual, data associated with preferences of the individual including determining data that is relevant to the activity, generating a profile for the individual based at least in part on the historical data and the preference data, detecting a trigger event indicative of the individual being in a mode related to the activity, selecting information relevant to the activity, the profile, and the trigger event, and providing the selected information to the individual in response to detecting the trigger event.

Abstract: Methods, systems, and computer program products are provided for tracking user interactions with interfaces and determining social data. One example method includes receiving from an entity an indication of interfaces that are used to interact with users, registering the user interfaces, tracking user interaction with the interfaces, and using the tracking information to determine all actions associated with a given user that are to be attributed to the entity.

Abstract: A system searches a first search index based on a search query to obtain first search results and searches a second search index based on the search query to obtain second search results. The system further ranks the first search results using a first ranking algorithm and one or more first ranking parameters to produce ranked first search results, and ranks the second search results using a second ranking algorithm and one or more second ranking parameters to produce second search results, where the one or more first ranking parameters are different than the one or more second ranking parameters and where the one or more second ranking parameters include at least one of previous user feedback associated with custom content that corresponds to the second search index, annotations of the custom content provided by a user, or usage patterns associated with users previously accessing and searching the custom content. The system also provides the ranked first and second search results to a user.

Abstract: In one aspect, methods include receiving one or more first bids that have associated fixed prices, receiving one or more second bids that have dynamic prices that are adjusted at a time of auction in consideration of other bids in the auction, conducting an auction including pricing the one or more first bids and the one or more second bids, the one or more first bids being priced at their respective fixed prices and the one or more second bids being priced at respective amounts that maintain each second bid in a position marginally above a next-highest bid in the auction, and serving content based on one or more winning bids from the auction.

Abstract: A system may store information regarding a set of items of content, receive sample content from a user, determine whether the sample content matches content of one or more of the items of content, and notify the user whether the sample content matches one or more of the items of content without identifying the one or more items of content to the user.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for location centric user profiling and services. In one aspect, a method includes accessing historical location data specifying physical locations at which user devices were detected; accessing network data for each of the users of the user devices, the network data for each user indicative of subjective preferences of the user; for each of the users, determining physical locations specified by the location data, determining entities from the physical locations and visited by the user, determining for each entity a satisfaction measure that is indicative of a satisfaction of the user with the entity, and generating a user profile for the user specifying topics that are of interest to the user, the entities having been determined to have been visited by the user, and the satisfaction measures of the entities.

Abstract: A device may select an advertisement in response to a search query, where the advertisement is selected based on a custom content search index. The device may further provide the selected advertisement for display with custom content search results generated based on the custom content search index.

Abstract: A bid for a content slot from a content provider is received. The bid includes a revenue-sharing bid. It is determined that the bid is a winning bid and content is presented from the content provider in the content slot. Presentation details are logged that include a time when the content was presented. At a later time, an indication is received of an action, the indication including an indication that the action is responsive to the content having been presented previously. Based on the action, the content provider is charged an appropriate amount based on the revenue sharing bid.

Abstract: The price of digital content is set by a pricing module using data obtained from a statistics module. The statistics module includes historical information about a content author's previous works, including demand for those works, and tracks data such as how many downloads are requested for the current content being priced, how many users are watching or listening to previews of the digital content, and where users are located. The pricing module may make content available for free initially; alternatively an initial non-zero price is chosen. The pricing module increases the price and observes changes in demand to determine a best-fit demand curve. Once the best-fit demand curve is determined, a price for the content is selected to maximize revenue. As the demand curve shifts, the price is adjusted to maintain optimal demand. Price is also adjusted proactively based on demand predictions determined according to statistical and historical data.

Abstract: In one aspect, methods include receiving one or more first bids that have associated fixed prices, receiving one or more second bids that have dynamic prices that are adjusted at a time of auction in consideration of other bids in the auction, conducting an auction including pricing the one or more first bids and the one or more second bids, the one or more first bids being priced at their respective fixed prices and the one or more second bids being priced at respective amounts that maintain each second bid in a position marginally above a next-highest bid in the auction, and serving content based on one or more winning bids from the auction.

Abstract: A query prefix is received from a user device. A user identifier is determined based on the user device. A user category is determined based on the user identifier. A node representing the query prefix is located in a query graph. Descendent nodes of the located node that represent queries are located. Each node has one or more user category specific frequency measures and each user category specific frequency measure is associated with a user category. The queries represented by the located nodes are ranked based on the associated user category specific frequency measure associated with the identified user category. The ranked queries are sent to the user device.

Abstract: Methods, systems, and computer program products are provided for tracking user interactions with interfaces and determining social data. One example method includes receiving from an entity an indication of interfaces that are used to interact with users, registering the user interfaces, tracking user interaction with the interfaces, and using the tracking information to determine all actions associated with a given user that are to be attributed to the entity.

Abstract: In general, first bids associated with an ad request are identified, where the first bids have an auction value that is set at a bidding time. Second bids associated with the ad request are identified, where the second bids have an auction value that is unknown at the bidding time. One or more predicted auction values for the second bids are determined, and an auction is run to identify one or more winning bids from the first and second bids for satisfying the ad request.

Abstract: A query prefix is received from a user device. A user identifier is determined based on the user device. A user category is determined based on the user identifier. A node representing the query prefix is located in a query graph. Descendent nodes of the located node that represent queries are located. Each node has one or more user category specific frequency measures and each user category specific frequency measure is associated with a user category. The queries represented by the located nodes are ranked based on the associated user category specific frequency measure associated with the identified user category. The ranked queries are sent to the user device.