Abstract: A method for reserving and provisioning IT resources comprises receiving, from a user, a request to reserve a desired configuration of IT resources. The desired configuration comprises one or more desired technical specifications and a desired reservation time having a start time and an end time. The method further comprises accessing an IT resource database to determine one or more of a plurality of resource pools that the user has access to. The one or more resource pools are consulted to determine if one or more IT resources matching the desired configuration are available. If the one or more IT resources matching the desired configuration are available, the one or more IT resources are reserved for the user and provided to the user at the start time.

Abstract: The invention provides a classification engine for classifying documents that makes use of functions included in a similarity search engine. The classification engine executes a classify command from a client that makes use of similarity search results, and rules files, classes files, and a classification profile embedded in the classification command. When the classification receives a classify command from a client, it retrieves a classification profile and input documents to be classified, sends extracted values from the input documents based on anchor values to a XML transformation engine to obtain a search schema, requests a similarity search by a search manager to determine the similarity between input documents and anchor values, and classifies the input documents according to the rules files, classes files, and the classification profile. The client is then notified that the classify command has been completed and the classification results are stored in a database.

Abstract: The invention provides a classification engine for classifying documents that makes use of functions included in a similarity search engine. The classification engine executes a classify command from a client that makes use of similarity search results, and rules files, classes files, and a classification profile embedded in the classification command. When the classification receives a classify command from a client, it retrieves a classification profile and input documents to be classified, sends extracted values from the input documents based on anchor values to a XML transformation engine to obtain a search schema, requests a similarity search by a search manager to determine the similarity between input documents and anchor values, and classifies the input documents according to the rules files, classes files, and the classification profile. The client is then notified that the classify command has been completed and the classification results are stored in a database.

Abstract: Attributes of a data set to be employed in generating a predictive model are analyzed based on entropy, chi-square, or similar statistical measure. A target group of samples exhibiting one or more desired attributes is identified, then remaining attribute values for the target group are compared to corresponding attribute values for the whole sample population. A subset of all available attributes is then selected from those attributes which exhibit, when comparing attribute values of target group samples to attribute values for the whole sample population, the greatest relative difference or divergence. This subset is employed to generate the predictive model. Efficiency in generating the predictive model and the accuracy of the resulting predictive model is improved, since fewer attributes are employed and less computational resources are required.

Abstract: The invention provides a classification engine for classifying documents that makes use of functions included in a similarity search engine. The classification engine executes a classify command from a client that makes use of similarity search results, and rules files, classes files, and a classification profile embedded in the classification command. When the classification receives a classify command from a client, it retrieves a classification profile and input documents to be classified, sends extracted values from the input documents based on anchor values to a XML transformation engine to obtain a search schema, requests a similarity search by a search manager to determine the similarity between input documents and anchor values, and classifies the input documents according to the rules files, classes files, and the classification profile. The client is then notified that the classify command has been completed and the classification results are stored in a database.

Abstract: A method for incorporating human arbitration into an otherwise automated workflow process for the purpose of classifying documents. Workflow management for document classification processes enables users to manage a process by arranging complex tasks into predefined sequences with decision points that steer tasks to completion. The method enables human arbitration of the workflow processes for document classification by providing a browser based user interface for arbitrating document classification processes. A software implemented system for browser-based arbitration in a classification workflow process comprising authenticating a user name and password for enabling a user logon, displaying a task list screen, the task list screen displaying a summary list containing each current task that the user has permission to view and links to a task detail screen, a search form screen, and a search queue screen, and enabling the user to arbitrate an assigned classification of assigned tasks in the workflow process.

Abstract: The invention provides a classification engine for classifying documents that makes use of functions included in a similarity search engine. The classification engine executes a classify command from a client that makes use of similarity search results, and rules files, classes files, and a classification profile embedded in the classification command. When the classification receives a classify command from a client, it retrieves a classification profile and input documents to be classified, sends extracted values from the input documents based on anchor values to a XML transformation engine to obtain a search schema, requests a similarity search by a search manager to determine the similarity between input documents and anchor values, and classifies the input documents according to the rules files, classes files, and the classification profile. The client is then notified that the classify command has been completed and the classification results are stored in a database.