Abstract: A system may receive an entity identifier for a user. The entity identifier may identify an entity that is associated with a category. The system may identify channel(s) for the category by obtaining data for the user, and analyzing the data to determine a score for each channel. The system may use the scores to select one or more of the channels. The system may provide content related to the selected channel(s) to a client device of the user, and the user may interact with the content via the client device.

Abstract: A user conducts activities, such as researching a product online or visiting a store that sells the product. A user then utilizes a risk analysis system to receive and store user activity data for the user's activities. When a purchase attempt is made with the user's financial account, a merchant sends a transaction request to the risk analysis system. The risk analysis system locates a record for the user and determines whether the product is identified in the user activity data. If the product is identified, the risk analysis system provides a risk score to the merchant indicating that the transaction is unlikely fraudulent. Alternatively, identification of the product provides a positive factor among multiple factors considered in a transaction risk analysis. An absence of the product in the activity can be used as a neutral or negative factor among multiple factors considered in a risk analysis of the transaction.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving data that represents actions taken by a particular user with respect to entities of a plurality of entity types, disambiguating the data by identifying entities specified in the data using a machine learning based annotator that is trained to recognize entities and annotating the data, receiving a query specific from the particular user, querying the data that represents actions taken by the particular user, generating an answer to the query from the data representing the actions taken by the particular user, and providing the answer to the query.

Abstract: A system may receive an entity identifier for a user. The entity identifier may identify an entity that is associated with a category. The system may identify channel(s) for the category by obtaining data for the user, and analyzing the data to determine a score for each channel. The system may use the scores to select one or more of the channels. The system may provide content related to the selected channel(s) to a client device of the user, and the user may interact with the content via the client device.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving data that represents actions taken by a particular user with respect to entities of a plurality of entity types, disambiguating the data by identifying entities specified in the data using a machine learning based annotator that is trained to recognize entities and annotating the data, receiving a query specific from the particular user, querying the data that represents actions taken by the particular user, generating an answer to the query from the data representing the actions taken by the particular user, and providing the answer to the query.

Abstract: A system may receive an entity identifier for a user. The entity identifier may identify an entity that is associated with a category. The system may identify channel(s) for the category by obtaining data for the user, and analyzing the data to determine a score for each channel. The system may use the scores to select one or more of the channels. The system may provide content related to the selected channel(s) to a client device of the user, and the user may interact with the content via the client device.

Abstract: A system is configured to obtain data for a user. The data may describe actions that the user has performed in an application and identify points in time associated with the actions. A point in time may include a point in time at which one of the actions was performed. The system is configured to analyze the data to determine, for each action, a score for each point in time. The score, for a particular point in time, may be determined based on one or more points in time at which the action was performed, and may be determined from a number of times that the action was performed at the particular point in time. The system is configured to provide the user with a functionality to perform a particular action based on the scores determined for the particular action for the set of points in time.

Abstract: A user conducts activities, such as researching a product online or visiting a store that sells the product. A user then utilizes a risk analysis system to receive and store user activity data for the user's activities. When a purchase attempt is made with the user's financial account, a merchant sends a transaction request to the risk analysis system. The risk analysis system locates a record for the user and determines whether the product is identified in the user activity data. If the product is identified, the risk analysis system provides a risk score to the merchant indicating that the transaction is unlikely fraudulent. Alternatively, identification of the product provides a positive factor among multiple factors considered in a transaction risk analysis. An absence of the product in the activity can be used as a neutral or negative factor among multiple factors considered in a risk analysis of the transaction.

Abstract: A system may identify one or more actions performed by a user to satisfy an intent for information regarding an entity; and determine a correlation score for the one or more actions. The correlation score may indicate a level of correlation between the one or more actions and satisfying the intent for the information regarding the entity. The system may determine that the correlation score satisfies a first threshold; obtain information identifying one or more changes associated with the entity; and determine a change score for the one or more changes. The change score may indicate a level of change that is associated with the entity. The system may determine that the change score satisfies a second threshold; and provide the information identifying the one or more changes to the user based on the correlation score satisfying the first threshold and the change score satisfying the second threshold.

Abstract: A user conducts activities, such as researching a product online or visiting a store that sells the product. A user then utilizes a risk analysis system to receive and store user activity data for the user's activities. When a purchase attempt is made with the user's financial account, a merchant sends a transaction request to the risk analysis system. The risk analysis system locates a record for the user and determines whether the product is identified in the user activity data. If the product is identified, the risk analysis system provides a risk score to the merchant indicating that the transaction is unlikely fraudulent. Alternatively, identification of the product provides a positive factor among multiple factors considered in a transaction risk analysis. An absence of the product in the activity can be used as a neutral or negative factor among multiple factors considered in a risk analysis of the transaction.

Abstract: A system may receive an entity identifier for a user. The entity identifier may identify an entity that is associated with a category. The system may identify channel(s) for the category by obtaining data for the user, and analyzing the data to determine a score for each channel. The system may use the scores to select one or more of the channels. The system may provide content related to the selected channel(s) to a client device of the user, and the user may interact with the content via the client device.

Abstract: A method, computer program product, and computing system for the sharing of experiences is provided. The method may include receiving content associated with a uniform resource locator and determining two or more content items based on the content associated with the uniform resource locator. The method may further include generating, based on the two or more content items, an experience data card and storing the generated experience data card in an experience data store, the experience data store being communicatively coupled to the one or more computing devices. The method may further include receiving a request to view the experience data card and providing for display, using the one or more computing devices, a view of the experience data card based at least in part on the request to view the experience data card.

Abstract: A user conducts activities, such as researching a product online or visiting a store that sells the product. A user then utilizes a risk analysis system to receive and store user activity data for the user's activities. When a purchase attempt is made with the user's financial account, a merchant sends a transaction request to the risk analysis system. The risk analysis system locates a record for the user and determines whether the product is identified in the user activity data. If the product is identified, the risk analysis system provides a risk score to the merchant indicating that the transaction is unlikely fraudulent. Alternatively, identification of the product provides a positive factor among multiple factors considered in a transaction risk analysis. An absence of the product in the activity can be used as a neutral or negative factor among multiple factors considered in a risk analysis of the transaction.

Abstract: A user conducts activities, such as researching a product online or visiting a store that sells the product. A user then utilizes a risk analysis system to receive and store user activity data for the user's activities. When a purchase attempt is made with the user's financial account, a merchant sends a transaction request to the risk analysis system. The risk analysis system locates a record for the user and determines whether the product is identified in the user activity data. If the product is identified, the risk analysis system provides a risk score to the merchant indicating that the transaction is unlikely fraudulent. Alternatively, identification of the product provides a positive factor among multiple factors considered in a transaction risk analysis. An absence of the product in the activity can be used as a neutral or negative factor among multiple factors considered in a risk analysis of the transaction.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for obtaining information to provide to users. One of the methods includes receiving a plurality of entities for a first user, wherein each of the plurality of entities is associated with a first score, wherein the first score associated with a particular entity represents a level of confidence that the first user is interested in the particular entity; and for one or more first entities of the plurality of entities: determining a second score based on the first score for the entity, wherein the second score indicates a level of confidence that the first user should receive notifications associated with the entity; determining that the second score satisfies a threshold; obtaining information associated with the entity; and providing the information to be presented in the form of a notification to the first user.

Abstract: A user conducts activities, such as researching a product online or visiting a store that sells the product. A user then utilizes a risk analysis system to receive and store user activity data for the user's activities. When a purchase attempt is made with the user's financial account, a merchant sends a transaction request to the risk analysis system. The risk analysis system locates a record for the user and determines whether the product is identified in the user activity data. If the product is identified, the risk analysis system provides a risk score to the merchant indicating that the transaction is unlikely fraudulent. Alternatively, identification of the product provides a positive factor among multiple factors considered in a transaction risk analysis. An absence of the product in the activity can be used as a neutral or negative factor among multiple factors considered in a risk analysis of the transaction.

Abstract: User commentary concerning a user experience is received and a user experience data card is generated for the user experience based, at least in part, upon the user commentary. The user experience data card is stored, wherein the stored user experience data card corresponds to a first view of the user experience data card and receiving a request for an experience data card from a second user. The user experience data card is provided to the second user at least in part based on the request received from the second user and receiving feedback from the second user concerning the user experience data card. A second view of the user experience data card is generated based, at least in part, upon the feedback from the second user, wherein the second view of the user experience data card is distinct form the first view of the experience data card.

Abstract: A method, computer program product, and computing system for receiving, on the one or more computing devices, a location indication from a user concerning a chosen location for potential experiences. A time indication is received, on the one or more computing devices, from the user concerning a time frame for the potential experiences. An experiences database is queried to identify two or more experiences that may be sequentially performed within the defined time period at the chosen location. An itinerary is generated, on the one or more computing devices, for the user based, at least in part, upon the two or more experiences.

Abstract: A system is configured to receive profile data for a user. The profile data may include user attributes. The profile data may include information regarding time intervals during which the user is available. The system is configured to receive a set of activity identifiers that identify activities in which the user can participate. Each of the activities may be associated with activity attributes. The activity attributes may identify one or more points in time at which the activity will occur. The system is configured to determine a correlation score for each activity of the activities. The correlation score for the activity may be determined from a correlation between the activity attributes associated with the activity and the profile data for the user. The system is configured to notify the user about one or more of the activities based on the correlation scores for the one or more activities.

Abstract: A system is configured to receive individual identifiers that identify a set of individuals; obtain respective profile data for each of the set of individuals; and determine a set of activity identifiers that identify activities in which the set of individuals can participate. Each of the activities may be associated with one or more activity attributes. The system is configured to determine a correlation score for each activity of the activities. The correlation score, for the activity, may be determined from a correlation between the one or more activity attributes associated with the activity and the respective profile data for the set of individuals. The system is configured to provide information identifying one or more of the activities based on the correlation scores determined for the one or more activities.