Abstract: A computer implemented method, apparatus, and computer usable program code for automatically selecting an optimal control cohort. Attributes are selected based on patient data. Treatment cohort records are clustered to form clustered treatment cohorts. Control cohort records are scored to form potential control cohort members. The optimal control cohort is selected by minimizing differences between the potential control cohort members and the clustered treatment cohorts.

Abstract: A system for implementing a multi objective evolutionary algorithm (MOEA) on a programmable hardware device is provided. The system comprises a random number generator, a population generator, a crossover/mutation module, a fitness evaluator, a dominance filter and an archive. The random number generator is configured to generate a sequence of pseudo random numbers. The population generator is configured to generate a population of solutions based on the output from the random number generator. The crossover/mutation module is configured to adapt the population of solutions to generate an adapted population of solutions. The fitness evaluator is configured to evaluate each member comprising the population of solutions and the adapted population of solutions. The fitness evaluator is implemented on the programmable hardware device.

Abstract: A method for assigning state codes to states of a state diagram embodying a plurality of signatures to be searched for in an input string of characters re-organizes the states of a search tree embodying the signatures to construct a failure tree in which the states are organized in levels according to a number of failure transitions between each state and the root node of the search tree.

Abstract: A system for and method of constructing an executable reusable procedure which includes determining an executable procedure from at least one scored trace of a procedure execution.

Abstract: Behavioral influences are determined and real-world variables modified according to the present invention. A forecasting engine and method assists in forecasting occurrences of identifiable events and/or results based on signature and/or pattern matching. The present invention derives signature for event-types based on a comparison of actual event data with pre-established representational surfaces. The surfaces represent functional measurements and analysis associated with elements of the geospatial boundary being considered. In one embodiment, the present invention assists in the determination of possible real-world factor influence opportunities in order to influence desired behavior.

Abstract: In certain embodiments of a cognitive radio, a method of establishing operational policies, involves determining that a new policy decision should be made; requesting a policy decision from an authority having more computing power than the cognitive radio; receiving the policy decision from the authority; and implementing the policy decision in the cognitive radio. Other embodiments may incorporate more, fewer or other elements.

Abstract: Various embodiments of a system and method for adapting software elements based on application usage are described. The system and method for adapting software elements based on application usage may include a knowledge component configured to determine how a user is using an interview-based application including, but not limited to, the functions of the application that the user has utilized, the content that the user has viewed, the tasks that have been performed, and the assistance that has been requested. The knowledge component may use the application usage to determine a measure of the user's knowledge of topics within an interview-based application in order to create and/or maintain a knowledge profile for the user. The knowledge component may use the user's knowledge profile to determine a knowledge deficiency that prevents the user from completing a task within the interview-based application and modify the application in order to resolve the deficiency.

Abstract: A method for controlling a game character is provided. The method includes analyzing a game situation in which a character appears; and controlling a behavior of the character depending on a result of the analyzing. Accordingly, situation recognition and behavior control depending on the recognized situation are simultaneously performed using the same algorithm, so that the calculation amount can be reduced, and thus high artificial intelligence can be implemented with less computer resources. Also, a game developer does not need to implement individual behavior rules of characters depending on game situations since a situation of the game may be recognized through learning of an artificial neural network using a game database of game situations, and thus the behavior of characters can be controlled depending on the recognized situation.

Abstract: A system, method, data processing apparatus, and article of manufacture are provided for classifying data. Labeled data points are received, each of the labeled data points having at least one label indicating whether the data point is a training example for data points for being included in a designated category or a training example for data points being excluded from a designated category; receiving unlabeled data points; receiving at least one predetermined cost factor of the labeled data points and unlabeled data points; training a transductive classifier using MED through iterative calculation using the at least one cost factor and the labeled data points and the unlabeled data points as training examples; applying the trained classifier to classify at least one of the unlabeled data points, the labeled data points, and input data points; and outputting a classification of the classified data points, or derivative thereof.

Abstract: Techniques enable a user, such as a business analyst or a system administrator, to define business process rules that control the processing of transaction data by a computer application and to assign a collection of business process rules to one of multiple predefined points in a business process of a computer application. At runtime, when the computer system executing the computer application reaches a point in a business process that is associated with a collection of user-defined business process rules, the computer system executes the business process rules. In this manner, a customized process represented by user-defined business process rules is able to be added to a computer application.

Abstract: Techniques enable a user, such as a business analyst or a system administrator, to define business process rules that control the processing of transaction data by a computer application. A data structure is used to store business process rules. The data structure includes a condition portion and an execution portion of a rule. At runtime, the computer system executing a computer application determines whether a condition portion of a rule is met, and in response to a determination that the condition portion is met, performs an execution portion of the rule.

Abstract: Techniques enable a user, such as a business analyst or a system administrator, to define business process rules that control the processing of transaction data by a computer application. A data structure is used to store business process rules. The data structure includes a condition portion and an execution portion of a rule. A rule may be associated with an external execution point, which, in turn, is associated with an application execution point in the transaction process. At runtime, the computer system executing a computer application when determines that an application execution point is reached, the computer system determines whether there is an external execution point associated with the application execution point, and if so, executes the execution portion of a rule associated with the external execution point if the condition portion of the rule is met.

Abstract: Systems, methods, and other embodiments associated with identifying and selectively deleting duplicate search results are described. One example system embodiment includes logic to receive an identity indicator from a search logic. The identity indicator is associated with a search item that the search logic determines to be relevant to a search request. The example system may also include logic to determine whether the search result associated with the identity indicator is a duplicate result based on comparing the identity indicator to another identity indicator associated with another search result.

Abstract: A method and apparatus are disclosed for modeling a system to estimate values and associated uncertainties for a first set of variables describing the system. A second set of system variables is selected, where the second set is directly or indirectly causally related to the first set of variables. Data is obtained or estimated for each variable in the second set and the quality of selected data is appraised. A network is formed with nodes including both sets of variables and the quality appraisals, having directional links connecting interdependent nodes, the directional links honoring known causality relationships. A Bayesian Network algorithm is used with the data and quality information to solve the network for the first set of variables and their associated uncertainties.

Abstract: A system is described for automatically invoking computational resources without intervention or request from a user of the system. The computational resources may operate by searching across a network, or may themselves be located across a network. In the system a query-free information retrieval system is described in which the exact technical documentation contained in existing user or other technical manuals is provided to a user investigating apparatus having a fault. The user enters symptoms based upon the user's analysis of the apparatus, and in response the system provides information concerning likely faults with the apparatus. As the symptoms are entered, to relative value of individual faults is determined and related to the symptoms they cause. The user can then select technical information relating to probable faults in the system.

Abstract: The invention involves generating and presenting, typically electronically, a number of design alternatives to persons who are participating in the design, selection, or market research exercise. The participants (referred to as “selectors”) transmit data indicative of their preferences among or between the presented design alternatives, and that data is used to derive a new generation of design alternatives or proposals. The new designs are generated through the use of a computer program exploiting a genetic or evolutionary computational technique. The process is repeated, typically for many iterations or cycles.

Abstract: A system and method of identifying loose patterns using a smart multiset intersection operation are provided. Data segments are received from a data segmentation algorithm and sorted into corresponding multisets. A retain operation may be performed on the multisets. A normalization operation is then performed on the repeating elements in the multisets to identify the loose pattern. The loose pattern is stored in a database.

Abstract: Methods and apparatus are provided for generating a decision trees using linear discriminant analysis and implementing such a decision tree in the classification (also referred to as categorization) of data. The data is preferably in the form of multidimensional objects, e.g., data records including feature variables and class variables in a decision tree generation mode, and data records including only feature variables in a decision tree traversal mode. Such an inventive approach, for example, creates more effective supervised classification systems. In general, the present invention comprises splitting a decision tree, recursively, such that the greatest amount of separation among the class values of the training data is achieved. This is accomplished by finding effective combinations of variables in order to recursively split the training data and create the decision tree. The decision tree is then used to classify input testing data.

Abstract: Systems and methods for determining semantically related terms using an active learning framework such as Transductive Experimental Design are disclosed. Generally, to enhance a keyword suggestion tool, an active learning module trains a model to predict whether a term is relevant to a user. The model is then used to present the user with terms that have been determined to be relevant based on the model so that an online advertisement service provider may more efficiently provide a user with terms that are semantically related to a seed set.

Abstract: Methods, systems and computer program products for identifying primary product objects on a web page. A primary product object is the object that shows the best view of the product the web page is detailing. A set of features is extracted for one or more objects on the web page. The primary product objects are identified by computing the probabilities of one or more objects on the web page being a primary product object, the probabilities indicating the likelihood of the one or more objects being the primary product object. The probabilities are computed by querying a statistical model.