Abstract: The present disclosure discusses the adjustment of a rate of display between different types of content item categories. The system of the present disclosure can determine a content item's rate of display with a first category of content and with a second category of content. The system can determine a relationship between the display rates. If the display rates are outside of a predetermined range, the system can update the display parameters of the content categories.

Abstract: A computing system can detect a session trigger corresponding to execution of a service application on a computing device of a user, the session trigger initiating a user session of an application-based service. The system can execute one or more of a plurality of models corresponding to a unique objective for the application-based service, wherein each model runs real-time session data corresponding to the user session. The system can generate, from each model of the plurality of models, a session score indicating a priority level for the unique objective corresponding to the model. Based on the session score from each of the plurality of models, the system can transmit treatment data to the computing device of the user, the treatment data causing treatment content to be displayed on the computing device of the user.

Abstract: Systems and methods of the present disclosure are directed generally to facilitating content selection by identifying low impact criteria. In some implementations, a data processing system accesses a data structure storing, in a memory element, a plurality of impression records. Each impression record can include one or more features and an indication of user interest corresponding to a content impression. The data processing system can identify a combination feature based on at least two of the features. The data processing system can execute a statistical model (e.g., logistic regression model) using the impression records and the combination feature. The data processing system can determine a weight for the combination feature. Responsive to the weight being less than a threshold, the data processing system can transmit an indication to disable the combination feature for selecting content associated with the plurality of impression records.

Abstract: A network computer system maintains a service profile for each user in a population of users for a network service, where the service profile identifies multiple service parameters, and each service parameter of the service profile is based at least in part on one or more predefined usage events. The network computer system can identify a service signal in connection with providing the network service, where the service signal identifies an intent for a group of users. The network computer system can determine, using the service profile of individual users of the population, a group of users that is likely to include more users that are to perform an action in accordance with the intent of the service signal, as compared to a baseline value.

Abstract: The present disclosure discusses the adjustment of a rate of display between different types of content item categories. The system of the present disclosure can determine a content item's rate of display with a first category of content and with a second category of content. The system can determine a relationship between the display rates. If the display rates are outside of a predetermined range, the system can update the display parameters of the content categories.

Abstract: Systems and methods of the present disclosure are directed generally to facilitating content selection by identifying low impact criteria. In some implementations, a data processing system accesses a data structure storing, in a memory element, a plurality of impression records. Each impression record can include one or more features and an indication of user interest corresponding to a content impression. The data processing system can identify a combination feature based on at least two of the features. The data processing system can execute a statistical model (e.g., logistic regression model) using the impression records and the combination feature. The data processing system can determine a weight for the combination feature. Responsive to the weight being less than a threshold, the data processing system can transmit an indication to disable the combination feature for selecting content associated with the plurality of impression records.

Abstract: A dispatch system is provided to collect and store historical passenger pick-up and drop-off data. The dispatch system can utilize the historical data to construct correlation models that identify spike pairs each comprising a spike in passenger drop-offs and an associated spike in passenger pick-ups at a given location. The spike pairs can be indicative of an event at an event location having a typical duration. The dispatch system can detect a current spike in passenger drop-offs at a respective event location, and predict an associated spike in pick-up requests after a given duration at the event location using the historical data and correlation models.

Abstract: A computing device automatically customizes attributes of a graphical keyboard based on user inputs to the graphical keyboard. For example, the computing device can display a first graphical keyboard arrangement that includes a first representation of a key associated with a target region of an input-sensitive display. The computing device receives a plurality of user inputs, each associated with a respective touch region of the input-sensitive display. Subsequent to determining that one or more of the touch regions is not substantially aligned with the target region, the computing device displays a second graphical keyboard arrangement that includes a second representation of the key, wherein at least one attribute of the second representation of the key is graphically modified relative to the first representation of the key so as to substantially align one or more of the touch regions with a target region associated with the second representation of the key.

Abstract: A computing device automatically customizes attributes of a graphical keyboard based on user inputs to the graphical keyboard. For example, the computing device can display a first graphical keyboard arrangement that includes a first representation of a key associated with a target region of an input-sensitive display. The computing device receives a plurality of user inputs, each associated with a respective touch region of the input-sensitive display. Subsequent to determining that one or more of the touch regions is not substantially aligned with the target region, the computing device displays a second graphical keyboard arrangement that includes a second representation of the key, wherein at least one attribute of the second representation of the key is graphically modified relative to the first representation of the key so as to substantially align one or more of the touch regions with a target region associated with the second representation of the key.

Abstract: A computing device automatically customizes attributes of a graphical keyboard based on user inputs to the graphical keyboard. For example, the computing device can display a first graphical keyboard arrangement that includes a first representation of a key associated with a target region of an input-sensitive display. The computing device receives a plurality of user inputs, each associated with a respective touch region of the input-sensitive display. Subsequent to determining that one or more of the touch regions is not substantially aligned with the target region, the computing device displays a second graphical keyboard arrangement that includes a second representation of the key, wherein at least one attribute of the second representation of the key is graphically modified relative to the first representation of the key so as to substantially align one or more of the touch regions with a target region associated with the second representation of the key.

Abstract: A system for generating subphrase queries. The system includes a sequence label modeling engine and a regression modeling engine. The sequence label modeling engine generates a plurality of subphrase queries by indexing through each token in a search phrase and labeling each token based on an association to other tokens in the search phrase. The regression modeling engine scores each subphrase query at least partially on the association according to a scoring model. The regression modeling engine identifies the subphrase query with the highest score which may then be used for identifying a sponsored search list or a web search item.