Abstract: Embodiments provide for a computer system and method to employ a sequence invariant model to determine user intentions, based on monitoring of real-time activities of the user.

Abstract: In some examples, the designated set of resources are subsequently monitored for session activities of multiple users that are not of the first group. For each of the multiple users, the computer system utilizes one or more predictive models to determine a likelihood of the user performing a desired type of activity based on one or more session activities detected for that user.

Abstract: In some examples, the designated set of resources are subsequently monitored for session activities of multiple users that are not of the first group. For each of the multiple users, the computer system utilizes one or more predictive models to determine a likelihood of the user performing a desired type of activity based on one or more session activities detected for that user.

Abstract: A computer system develops models and generates decision logic based on the developed models. The decision logic is distributed to end user devices, and the end user devices are able to implement the decision logic to detect events, determine event sequences, and correlate the determined event sequences to predicted outcomes.

Abstract: A weather intelligence system retrieves weather forecast data for a number of geographic regions. The weather intelligence system determines, using the weather forecast data for each of the geographic regions, a set of geographic regions predicted to experience a weather anomaly, or unusual weather condition, during a particular time interval. The weather intelligence system determines, through a machine-learning process, whether the weather forecast data indicates conditions that people would generally consider to be unusually hot or cold. The weather intelligence system can then programmatically enable a trigger to transmit a service-related offer associated with the weather anomaly to user devices located within one of the geographic regions where that weather anomaly is determined.

Abstract: A network computer system and method are provided in which each user of a group of users is monitored during a respective online session where the user performs a sequence of M activities, to selectively engage users of the group. A determination is made as to the impact of friction for each user of the group of users with respect to an intention of the respective user, and an action is performed for the user based at least in part on the determined impact of friction.

Abstract: Embodiments provide for a computer system and method to employ a sequence invariant model to determine user intentions, based on monitoring of real-time activities of the user.

Abstract: A computer system operates to detect a series of activities performed by a user, where the activities include interactions as between the user and one or more user interface components. The computer system recognizes the of activities as a sequence of events, where each event of the sequence corresponds to one more activities of the series. In response to the computer system detecting a current user activity, the computer system determines at least one of a user intent or interest based on an analysis of a relevant portion of the sequence of events.

Abstract: A computer system operates to detect a series of activities performed by a user, where the activities include interactions as between the user and one or more user interface components. The computer system recognizes the of activities as a sequence of events, where each event of the sequence corresponds to one more activities of the series. In response to the computer system detecting a current user activity, the computer system determines at least one of a user intent or interest based on an analysis of a relevant portion of the sequence of events.

Abstract: A weather intelligence system retrieves weather forecast data for a number of geographic regions. The weather intelligence system determines, using the weather forecast data for each of the geographic regions, a set of geographic regions predicted to experience a weather anomaly, or unusual weather condition, during a particular time interval. The weather intelligence system determines, through a machine-learning process, whether the weather forecast data indicates conditions that people would generally consider to be unusually hot or cold. The weather intelligence system can then programmatically enable a trigger to transmit a service-related offer associated with the weather anomaly to user devices located within one of the geographic regions where that weather anomaly is determined.

Abstract: In some examples, the designated set of resources are subsequently monitored for session activities of multiple users that are not of the first group. For each of the multiple users, the computer system utilizes one or more predictive models to determine a likelihood of the user performing a desired type of activity based on one or more session activities detected for that user.

Abstract: In some examples, the designated set of resources are subsequently monitored for session activities of multiple users that are not of the first group. For each of the multiple users, the computer system utilizes one or more predictive models to determine a likelihood of the user performing a desired type of activity based on one or more session activities detected for that user.

Abstract: A network computing system, and method for implementing a network computing system, to analyze events accumulated over digital channels of an enterprise, for purpose of determining contextual and/or customized outputs that facilitate a desired objective of the enterprise.

Abstract: A computer system operates to detect a series of activities performed by a user, where the activities include interactions as between the user and one or more user interface components. The computer system recognizes the of activities as a sequence of events, where each event of the sequence corresponds to one more activities of the series. In response to the computer system detecting a current user activity, the computer system determines at least one of a user intent or interest based on an analysis of a relevant portion of the sequence of events.

Abstract: A computer system develops models and generates decision logic based on the developed models. The decision logic is distributed to end user devices, and the end user devices are able to implement the decision logic to detect events, determine event sequences, and correlate the determined event sequences to predicted outcomes.

Abstract: In some examples, the designated set of resources are subsequently monitored for session activities of multiple users that are not of the first group. For each of the multiple users, the computer system utilizes one or more predictive models to determine a likelihood of the user performing a desired type of activity based on one or more session activities detected for that user.

Abstract: Software system facts comprising concepts, concept instances and relationships within the software system are identified and stored in a repository. The software system facts are extracted from artifacts comprising the software system or are provided through explicit definition. Architectures of the software system are recovered from the stored software system facts. Layered views of the recovered architectures are generated. The stored software system facts are checked against architectural rules to ensure architectural compliance of the software system. The impact of proposed changes to the software system is assessed by querying the identified software system facts.

Abstract: Software system facts comprising concepts, concept instances and relationships within the software system are identified and stored in a repository. The software system facts are extracted from artifacts comprising the software system or are provided through explicit definition. Architectures of the software system are recovered from the stored software system facts. Layered views of the recovered architectures are generated. The stored software system facts are checked against architectural rules to ensure architectural compliance of the software system. The impact of proposed changes to the software system is assessed by querying the identified software system facts.

Abstract: Versioning may be utilized in a knowledge base decision tree in order to provide several useful features. To accomplish this, when a decision tree is traversed, the decision tree representing a knowledge base and having non-leaf nodes with one or more branches representing possible symptoms, and leaf nodes with no branches, branches may be followed corresponding to symptoms experience by the application until a leaf node is reached. This traversal may be recorded as a version, with subsequent traversals having a different version. This allows a user to rerun performance tuning either from the beginning or from an earlier node without having to re-enter information already provided. It also allows a user to resume the performance tuning should he be interrupted in the middle, such as by a crash or by having to halt a long traversal.

Abstract: Versioning may be utilized in a knowledge base decision tree in order to provide several useful features. To accomplish this, when a decision tree is traversed, the decision tree representing a knowledge base and having non-leaf nodes with one or more branches representing possible symptoms, and leaf nodes with no branches, branches may be followed corresponding to symptoms experience by the application until a leaf node is reached. This traversal may be recorded as a version, with subsequent traversals having a different version. This allows a user to rerun performance tuning either from the beginning or from an earlier node without having to re-enter information already provided. It also allows a user to resume the performance tuning should he be interrupted in the middle, such as by a crash or by having to halt a long traversal.