Abstract: The current document discloses an automated method and system for inferring the logical rules underlying the configuration and versioning state of the components and subcomponents of a complex system, including data centers and other complex computational environments. The methods and systems employ a database of configuration information and construct an initial set of logical rules, or hypotheses, regarding system configuration. Then, using simulated annealing and a variant of genetic programming, the methods and systems disclosed in the current document carry out a search through the hypothesis state space for the system under several constrains in order to find one or more hypotheses that best explain the configuration and, when available, configuration history. The constraints include minimization of the complexity of the hypotheses and maximizing the accuracy by which the hypotheses predict observed configuration and configuration history.

Abstract: A computerized device for enhancing the accuracy of a question-answer system is disclosed. The computerized device comprises a question-answer system comprising software for performing a plurality of question answering processes. A receiver receives a question into the question-answer system. A processor that generates a plurality of candidate answers to the question is connected to the question-answer system. The processor determines a confidence score for each of the plurality of candidate answers. The processor evaluates sources of evidence used to generate the plurality of candidate answers. The processor identifies missing information from a corpus of data. The missing information comprises any information that improves a confidence score for a candidate answer. The processor generates at least one follow-on inquiry based on the missing information. A network interface outputs the at least one follow-on inquiry to external sources separate from the question-answer system.

Abstract: Embodiments of the invention build models to predict the likelihood of entities that operate in a given identifier space also operating in a disjoined identifier space based on a source panel of entities that operate in one or both of the identifier spaces. In operation, a model building engine builds a model based on features associated with the source panel and features associated with standard populations in the given identifier space. The model used to determine whether the target entity is more similar to those entities in the source panel that operate only in the given identifier space or those entities in the source panel that operate in both identifier spaces.

Abstract: A computer-based crime risk forecasting system and corresponding method are provided for generating crime risk forecasts and conveying the forecasts to a user. With the conveyed forecasts, the user can more effectively gauge both the level of increased crime threat and its potential duration. The user can then leverage the information conveyed by the forecasts to take a more proactive approach to law enforcement in the affected areas during the period of increased crime threat.

Abstract: A method, system, and process for generating attribute class statistics for a decision tree is discussed. In an embodiment the ACS's are calculated in parallel on a distributed architecture, and may consume a constant amount of resources.

Abstract: Methods and computer implemented systems for evaluation and optimisation of methods used for forecasting, modeling, valuation, and decision-making, in staged resource planning are provided. Fundamentally, a universal comparator that accounts for perfect decision differencing (PERNOB) is determined and used for evaluating benefits associated with the use of prediction method-sets and decision-making method-sets in staged resource planning. According to one application, PERNOB is used to evaluate different prediction method-sets and decision-making method-sets and enable the selection of optimal method-sets corresponding to a given situation. According to another application, PERNOB is used to create an unbiased operational decision making environment through realistic re-valuation of system resource(s).

Abstract: Techniques for aggregating hypotheses for use in data analytics. In one example, a method comprises the following steps. A plurality of hypotheses associated with one or more data analytics tasks are stored in a storage queue. Two or more hypotheses of the plurality of hypotheses are selected for aggregation. The selected two or more hypotheses are aggregated into a hypotheses group such that the selected two or more hypotheses of the hypothesis group are processed together using one or more common resources to perform at least one of the one or more data analytics tasks.

Abstract: A method for measuring volatility of usage based data. Usage based data are measureable parameters of a system and parameters in which the system operates in order to infer the manner in which the system is operated. The method allows for inferences regarding the operator or operators of the system and the environment in which it operates. This invention is described with reference to consumer automobiles and drivers in typical environments, primarily for application in the automobile insurance industry where measuring volatility to determine behavior. However, this method may be applied to other systems including commercial automobiles and trucks, motorcycles, all terrain automobiles, snow mobiles, water craft, air craft, space craft, assembly line operation, robotic devices, remote operational devices, and military automobiles. This method may also be applied to applications other than assessing risk including, but not limited to, marketing, profiling, sales, optimization, operations and control.

Abstract: A multifunctional neural network system for prediction which includes memory components to store previous values of data within a network. The memory components provide the system with the ability to learn relationships/patterns existent in the data over time.

Abstract: Certain embodiments of the invention may include systems and methods for identifying drug targets using biological networks. According to an example embodiment of the invention, a method is provided for predicting the effects of drug targets on treating a disease. The method can include constructing a structure of a Bayesian network based at least in part on knowledge of drug inhibiting effects on a disease; associating a set of parameters with the constructed Bayesian network; determining values of a joint probability distribution of the Bayesian network via an automatic procedure; deriving a mean Bayesian network with one or more averaged parameters based at least in part on the joint probability values; and calculating a quantitative prediction based at least in part on the mean Bayesian network.

Abstract: Some examples are directed to selecting at least one candidate solution from a first plurality of candidate solutions that has converged on a suboptimal solution during a computer simulation. The computer simulation tests fitness of the first plurality of candidate solutions for an optimization problem. Some examples are further direct to storing a copy of the at least one candidate solution, performing a cataclysm on the first plurality of candidate solutions, and generating a second plurality of candidate solutions. Some examples are further direct to integrating the copy of the at least one candidate solution into the second plurality of candidate solutions after performing of one or more additional computer simulations that test the fitness of the second plurality of candidate solutions for the optimization problem.

Abstract: A computerized device for enhancing the accuracy of a question-answer system. The computerized device comprises a question-answer system comprising software for performing a plurality of question answering processes. A receiver receives a question into the question-answer system. A processor that generates a plurality of candidate answers to the question is connected to the question-answer system. The processor determines a confidence score for each of the plurality of candidate answers. The processor evaluates sources of evidence used to generate the plurality of candidate answers. The processor identifies missing information from a corpus of data. The missing information comprises any information that improves a confidence score for a candidate answer. The processor generates at least one follow-on inquiry based on the missing information. A network interface outputs the at least one follow-on inquiry to external sources separate from the question-answer system.

Abstract: A method of enhancing the accuracy of a question-answer system. Missing information from a corpus of data is identified. The missing information is any information that improves a confidence for a candidate answer to a question. A follow-on inquiry is generated. The follow-on inquiry prompts for the missing information to be provided. The follow-on inquiry is output to an external source. A response to the follow-on inquiry is received from the external source. The response is added to the corpus of data.

Abstract: Techniques for evaluation and/or retraining of a classification model built using labeled training data. In some aspects, a classification model having a first set of weights is retrained by using unlabeled input to reweight the labeled training data to have a second set of weights, and by retraining the classification model using the labeled training data weighted according to the second set of weights. In some aspects, a classification model is evaluated by building a similarity model that represents similarities between unlabeled input and the labeled training data and using the similarity model to evaluate the labeled training data to identify a subset of the plurality of items of labeled training data that is more similar to the unlabeled input than a remainder of the labeled training data.

Abstract: Processing metadata includes storing, in a data storage system, a specification for each of multiple sources, each specification including information identifying one or more data elements of the corresponding source; and processing, in a data processing system coupled to the data storage system, data elements from the sources, including generating a set of rules for each source based on a corresponding one of the stored specifications, and matching data elements of different sources and determining a quality metric characterizing a given match between a first data element of a first source and a second data element of a second source according to the set of rules generated for the first source and the set of rules generated for the second source.

Abstract: A personal taste assessment and prediction system implements a method of predicting a person's preference for an item. The system may receive identifying information about an item of interest, and it may use the identifying information to access a database of characteristic values for various items and identify one or more characteristics of the item of interest. The system will access a user profile and process the retrieved characteristics with a user profile for a person to generate a predicted rating for the item of interest for the person.

Abstract: Systems and methods are disclosed for distributed first- or higher-order model fitting algorithms. Determination of the parameter set for the objective function is divided into a plurality of sub-processes, each performed by one of a plurality of worker computers. A master computer coordinates the operation of the plurality of worker computers, each operating on a portion of the parameter set such that no two worker computers contain exactly the same parameter subset nor the complete parameter set. Each worker computer performs its sub-processes on its parameter subset, together with training data. For maximum efficiency, the sub-processes are performed using a compact set of instruction primitives. The results are evaluated by the master computer, which may coordinate additional sub-process operations to perform higher-order optimization or terminate the optimization method and proceed to formulation of a model function.

Abstract: A method and apparatus for detection of relationships between objects in a meta-model semantic network is described. Semantic objects and semantic relations of a meta-model of business objects are generated from a meta-model semantic network. The semantic relations are based on connections between the semantic objects. A neural network is formed based on usage of the semantic objects and the semantic relations. The neural network is integrated with the semantic objects and the semantic relations to generate a contextual network. A statistical analysis of the connections between the semantic objects in the contextual network is performed to identify stronger semantic relations. The identified stronger semantic relations are used to update the neural network. The updated neural network is integrated into the contextual network.

Abstract: Systems and methods for determining a probability of changing from one state to another in a stochastic entity, comprising: determining the compact component matrix utilizing characteristic information of the stochastic entity; determining the compact composite component matrix by taking a Kroneker product of the compact component matrix and an identity matrix; determining and placing all current states for the stochastic entity into a state space matrix; determining a Q matrix and/or a transition rate matrix using the compact composite component matrix and basic conditions or variables of the problem domain and/or a compact transition rate matrix; and performing Markov chain Monte Carlo (MCMC) simulation using information from the state space matrix and information from the transition rate matrix to determine the probability of changing from one state to another state in the stochastic entity.

Abstract: A system and method for selecting a datum representative of an air parameter, including a plurality of sources each capable of delivering a datum representative of a measured value of the parameter. The system includes: a mechanism for determining, for at least some sources, a number of other sources from the plurality of sources in agreement with a source in question; and a mechanism for selecting the datum selected from the data delivered by the sources for which the determined agreement number is the maximum. An engine control system, or an aircraft can include such a system or implement such a method.