Systems and methods including one or more processing modules and one or more non-transitory storage modules storing computing instructions configured to run on the one or more processing modules and perform acts of: monitoring first activities of a user over a first time period; based on the first activities of the user over the first time period, identifying, using a Markov model, a first probability of the user being in a first state; determining when the first probability is above a first probability predefined threshold; in response to determining when the first probability is above the first probability predefined threshold, automatically customizing first content on a graphical user interface for the first state to create a first graphical user interface on an electronic device of the user while the user is determined to be in the first state; monitoring second activities of the user over a second time period occurring after the first time period and after the user has been determined to be in the first state and before the user has been determined to be in a second state; based on the second activities of the user over the second time period, identifying, using a mixed model different from the Markov model, a second probability that the user has transitioned from the first state into the second state, wherein the second state is related to the first state; determining when the second probability is above a second probability predefined threshold; and in response to determining when the second probability is above the second probability predefined threshold, automatically customizing a second content on the graphical user interface for the second state to create a second graphical user interface on the electronic device user while the user is determined to be in the second state. Other embodiments are disclosed herein.

Embodiments herein can determine an optimal route for an autonomous electric vehicle. The system may score viable routes between the start and end locations of a trip using a numeric or other scale that denotes how viable the route is for autonomy. The score is adjusted using a variety of factors where a learning process leverages both offline and online data. The scored routes are not based simply on the shortest distance between the start and end points but determine the best route based on the driving context for the vehicle and the user.

An advocacy system uses trained machine learning models to create messages that are sent to advocates or policymakers to achieve desired outcomes for an organization. Desired outcomes can include, for example: an advocate sending a message to a policymaker or legislative representative advocating in favor or the organization's position on an issue; a policymaker acting or voting in favor of the organization's position on an issue; or an advocate making a financial contribution to the organization. The machine learning models can be configured to select possible message characteristics or features that the system will include/use in creating/sending messages to/for individual senders and recipients. The machine learning models can be trained based on message characteristics, personal profile characteristics of senders/recipients, and outcomes from previously sent messages. Personal profile characteristics of senders/recipients can indicate correlations between certain message characteristics and certain outcomes of sending messages.

Systems and methods are described for providing an enhanced rebate and marketing program which may automatically enroll a consumer in a loyalty programs after the consumer completes rebate form; filter consumer information to provide to customer relationship management campaigns; capture real-time consumer responses to queries; provide real-time and dynamic, targeted offers and other communications to consumers and recipients; and provide bonus added value to consumer received rebates.

Location technologies are combined with other information systems to provide augmented information for individuals such as a traveler in an automobile.

Methods, systems, and apparatus include computer programs encoded on a computer-readable storage medium. A method includes: for each of a plurality of content items in an inventory of content items: identifying an entity associated with the content item and a plurality of page types for a vertical associated with a product or service described in the content item; locating a plurality of informational pages associated with the entity; classifying each informational page based on the page types; identifying queries associated with the entity, wherein a query is used as a selection criteria for delivering one or more content items associated with the entity; for each informational page of the plurality of informational pages determining relevant queries from the identified queries; and storing in a data structure an association between the content item, data associated with the relevant queries and associated informational pages.

Systems and methods for providing a first user with recommendations of media assets for inclusion in a playlist for a second user based on the second user's viewing activity. These systems and methods receive, from the second user, an expression of disinterest in a media asset included in the playlist for the second user, update a user profile associated with the second user based on the expression of disinterest, and determine a recommendation for another media asset based on the updated user profile associated with the second user. The systems and methods provide the recommendation to the first user. By recommending media assets that the second user is least likely to object to, these systems and methods reduce the frequency of disruptive requests for media assets from the second user.

A classification based notification system is disclosed which performs operations that include: accessing user profile data associated with a user account associated with a client device, the user profile data including a list of user connections; designating a notification type to a portion of the list of user connections, the notification type corresponding to an alert attribute; receiving a notification from a user connection from among the portion of the list of user connections at the client device; and presenting an alert based on the alert attribute that corresponds with the notification type associated with the portion of the list of user connections at the client device.

Aspects of the subject disclosure may include, for example, receiving information defining an attribute of interest for the impression, wherein the attribute of interest comprises a plurality of categories of values, and receiving information defining a respective probability for each respective value of the plurality of categories of values for the impression. Further, information about current values of the plurality of categories for the attribute of interest may be received and a pacing value may be determined based on the respective probability for each respective value of the plurality of categories of values, along with the information about current values the plurality of categories for the attribute of interest. A respective bid value of a bid may be adjusted using the pacing value and the adjusted bid value may be used in an auction to fill the impression. This permits automatic detection and correction of an inadvertent skew introduced when serving ads and other content. Other embodiments are disclosed.

To provide more useful additional information to the user at a more effective timing. Provided is an information processing apparatus including an output control unit that controls an output of additional information related to a product purchased by a user. The output control unit controls an output of the additional information on the basis of delivery information about the product. In addition, provided is an information processing method that is executed by a processor, the information processing method including controlling an output of additional information related to a product purchased by a user. The controlling of an output includes controlling an output of the additional information on the basis of delivery information about the product.