Abstract: An example method for generating a user profile for a user based on a static profile and a dynamic profile of the user includes compressing dynamic rules into aggregated rules for validation. The dynamic rules associated with a particular user are matched to one or more validated aggregated rules to generate the dynamic profile for that user. The static profile for the user is generated for the user based on factual user information and historical transactional data for the user. The static and dynamic profile are then combined to form the user profile.

Abstract: In one embodiment, a method includes accessing, by a computing device, at least a portion of a user profile that is based at least in part on historical data associated with a user and receiving, by a computing device, data indicative of a current state of the user from a remote system. The current state of the user is the user's current activity. The method also includes selecting, by a computing device, content by matching one or more attributes of the content to the portion of the user profile and the current state of the user and providing, by a computing device, the selected content for display to the user.

Abstract: An example method for generating a user profile for a user based on a static profile and a dynamic profile of the user includes compressing dynamic rules into aggregated rules for validation. The dynamic rules associated with a particular user are matched to one or more validated aggregated rules to generate the dynamic profile for that user. The static profile for the user is generated for the user based on factual user information and historical transactional data for the user. The static and dynamic profile are then combined to form the user profile.

Abstract: Particular embodiments provide functionality for predicting purchasing needs according to multidimensional data. The multidimensional data may define a multidimensional space. The multidimensional space may have at least three dimensions, and each of the dimensions may be capable of providing variable information, and/or having a type that is different from a type of another one of the dimensions. Particular embodiments may retrieve information from data associated with the multidimensional space. Predictions regarding purchasing needs may be generated based on the retrieved information. Purchasing recommendations may then be provided based on the predictions.

Abstract: Exemplary non-transitory computer-readable medium, method and system for providing at least one recommendation to users and applications using multidimensional data. The multidimensional data can define a multidimensional space defined by a Cartesian product of the dimensions. The multidimensional space can have at least three dimensions, and each of the dimensions can be capable of (i) providing variable information, and (ii) having a type that is different from a type of another one of the dimensions. The exemplary non-transitory computer-readable medium, method and system can retrieve information from data associated with the multidimensional space. Further, the exemplary non-transitory computer-readable medium, method and system can generate the at least one recommendation based on the retrieved information. Further, at least one of the dimensions can include profiles.

Abstract: A user specifies one or more monitoring/probing rules on a client station. These rules specify user instructions for monitoring and probing conditions, events and data on monitored sites on the Internet. The client station transfers the monitor/probing rules to the monitoring site which also processes and interprets the monitoring/probing rules. When the monitoring site processes these rules, it results in (1) an allocation of space and (2) the creation or initialization of agent programs, such that these agent programs will affect periodic monitoring of Internet sites and send data therefrom back to monitoring site. If the retrieved information at the monitoring site satisfies the user specified conditions, the monitoring site will conduct further exploration to gather more information which may help determine the causes of these conditions.

Abstract: A user specifies one or more monitoring/probing rules on a client station. These rules specify user instructions for monitoring and probing conditions, events and data on monitored sites on the Internet. The client station transfers the monitor/probing rules to the monitoring site which also processes and interprets the monitoring/probing rules. When the monitoring site processes these rules, it results in (1) an allocation of space and (2) the creation or initialization of agent programs, such that these agent programs will affect periodic monitoring of Internet sites and send data therefrom back to monitoring site. If the retrieved information at the monitoring site satisfies the user specified conditions, the monitoring site will conduct further exploration to gather more information which may help determine the causes of these conditions.

Abstract: A system and method for generating and validating a user profile (25) for a user based on a static profile (10) and a dynamic profile, (15) of the user. The method and system compresses the dynamic rules (15) into aggregated rules so that the user can view a comparatively small number of the aggregated rules and select the desired rules from the aggregated rules based on user-desired criteria. The method and system validates user rules (60) using a processing device, which are retrieved from a storage device. The user rules are separated into at least one subset of a user set. Then, it is determined if a particular rule of the at least one subset is one of acceptable, unacceptable and undecided based on a defined criteria (415). If the particular rules of the at least one subset are acceptable, the particular rules of the at least one subset are provided (e.g. assigned) to a corresponding user (435).

Abstract: A system and method for generating and validating a user profile (25) for a user based on a static profile (10) and a dynamic profile (15) of the user. The method and system compresses the dynamic rules (15) into aggregated rules so that the user can view a comparatively small number of the aggregated rules and select the desired rules from the aggregated rules based on user desired criteria. The method and system validates user rules (60) using a processing device, which are retrieved from a storage device. The user rules are separated into at least one subset of a user set. Then, it is determined if a particular rule of the at least one subset is one of acceptable, unacceptable and undecided based on a defined criteria (415). If the particular rules of the at least one subset are acceptable, the particular rules of the at least one subset are provided (e.g. assigned) to a corresponding user (435).

Abstract: A system and method for generating and validating a user profile (25) for a user based on a static profile (10) and a dynamic profile (15) of the user. The method and system compresses the dynamic rules (15) into aggregated rules so that the user can view a comparatively small number of the aggregated rules and select the desired rules from the aggregated rules based on user-desired criteria. The method and system validates user rules (60) using a processing device, which are retrieved from a storage device. The user rules are seperated into at least one subset of a user set. Then, it is determined if a particular rule of the at least one subset is one of acceptable, unacceptable and undecided based on a defined criteria (415). If the particular rules of the at least one subset are acceptable, the particular rules of the at least one subset are provided (e.g. assigned) to a corresponding user (435).

Abstract: A user specifies a hierarchical action tree via user input device and user interface element. The action tree is arranged in a tree of file directories, with each node of the tree corresponding to a file directory (or path). The user then specifies classes of patterns assigned to each node (directory) of the tree using data mining queries or pattern templates. Once the system is so initialized, the pattern templates and data mining queries are executed, retrieving the patterns specified by the user from a database. The retrieved patterns assigned to a node of the tree are then stored in a file in the corresponding file directory. The user may now act on the discovered patterns and use the organized file structure. A pattern discovery optimization element periodically checks if the database has changed substantially, and if it has re-executes the data mining queries and pattern templates which update the contents of the file structure accordingly.

Abstract: A system and method for generating a user profile for a user based on a static profile and a dynamic profile of the user. The static profile includes factual user information. The dynamic profile includes dynamic rules which correspond to transactional information of the user. The method and system compresses the dynamic rules into aggregated rules so that the user can view a comparatively small number of the aggregated rules and select the desired rules from the aggregated rules based on user-desired criteria. The dynamic rules associated with the particular user are matched to the selected desired aggregated rules to generate the dynamic profile. The static and dynamic profile are then combined to form the user profile. The system and method can be used in conjunction with a Personal Shopping Assistant system and a Personal Intelligent Digital Assistant system.