Abstract: A method and system for analyzing and optimizing the distribution of work from a plurality of queues includes storing historical data in a database. The historical data may include sets of different types of data items, each of the data items having an associated monetary value. The method further includes assigning a relative score to each of the data items within the sets and calculating a cumulative monetary value for each relative score, the cumulative monetary value being the summation of the monetary values for all items having relative scores up to and including the relative score. The method further includes determining the maximum cumulative monetary value calculated and its corresponding relative score. In one embodiment, the corresponding relative score is then used to determine which items to work in a set of queues that has not yet been worked.

Abstract: A system configured to forecast human behavior is provided. The system includes a memory storing information descriptive of a set of content including a plurality of elements, at least one processor coupled to the memory, and a plurality of components executable by at least one processor. The plurality of components include a mapping engine configured to retrieve the information associated with the set of content from the memory and generate a data space representative of relationships between the plurality of elements, a compression component configured to generate a customer compression representative of a behavior of at least one customer within the data space, a persuasion engine configured to identify at least one customer trajectory through the data space associated with the at least one customer based on at least the customer compression, and an interface component configured to provide output describing the at least one customer trajectory.

Abstract: A method and system for analyzing and optimizing the distribution of work from a plurality of queues includes storing historical data in a database. The historical data may include sets of different types of data items, each of the data items having an associated monetary value. The method further includes assigning a relative score to each of the data items within the sets and calculating a cumulative monetary value for each relative score, the cumulative monetary value being the summation of the monetary values for all items having relative scores up to and including the relative score. The method further includes determining the maximum cumulative monetary value calculated and its corresponding relative score. In one embodiment, the corresponding relative score is then used to determine which items to work in a set of queues that has not yet been worked.

Abstract: Systems and methods for presenting fraud detection information are presented. In one example, a computer system analyzes empirical data to detect potentially fraudulent activity and alerts users of the potentially fraudulent activity via a fraud detection user interface. The fraud detection user interface determines a set of user interface components to suitable to present the potentially fraudulent activity and presents facts associated with the potentially fraudulent activity to a user for further analysis and investigation.

Abstract: Systems and methods for presenting fraud detection information are presented. In one example, a computer system analyzes empirical data to detect potentially fraudulent activity and alerts users of the potentially fraudulent activity via a fraud detection user interface. The fraud detection user interface determines a set of user interface components to suitable to present the potentially fraudulent activity and presents facts associated with the potentially fraudulent activity to a user for further analysis and investigation.

Abstract: A method and system for analyzing and optimizing the distribution of work from a plurality of queues includes storing historical data in a database. The historical data may include sets of different types of data items, each of the data items having an associated monetary value. The method further includes assigning a relative score to each of the data items within the sets and calculating a cumulative monetary value for each relative score, the cumulative monetary value being the summation of the monetary values for all items having relative scores up to and including the relative score. The method further includes determining the maximum cumulative monetary value calculated and its corresponding relative score. In one embodiment, the corresponding relative score is then used to determine which items to work in a set of queues that has not yet been worked.