Abstract: At creation, a state machine of an industrial control configuration can be hard-coded with a number of states in a hierarchical manner. Once implemented into the configuration, it can be desirable for the states, interpretations of the states, and the like to be modified in accordance with particular desires and processes. Therefore, a user can select a change to a hierarchical rule set of the state machine while the state machine is part of the configuration and the change can be implemented.

Abstract: Systems, apparatus, and methods for correlating two items of interest, based on a plurality of data items and characteristics. The data items may include objective and quantitative data, as well as subjective and qualitative data. In one implementation, the relationship of an individual to a metric is determined. The system, apparatus, and methods may store characteristics describing individuals generally, along with metrics relevant to an organization; receive a plurality of data items; extract information associated with the individual from the data items; determine a number of relationships between the data items, individuals, metric, and characteristics; and use the relationships to determine an overall relationship between the individual and the metric, based on the data and characteristics. In addition, related groups of characteristics may be identified.

Abstract: Embodiments are described for a method for processing graph data by executing a Markov Clustering algorithm (MCL) to find clusters of vertices of the graph data, organizing the graph data by column by calculating a probability percentage for each column of a similarity matrix of the graph data to produce column data, generating a probability matrix of states of the column data, performing an expansion of the probability matrix by computing a power of the matrix using a Map-Reduce model executed in a processor-based computing device; and organizing the probability matrix into a set of sub-matrices to find the least amount of data needed for the Map-Reduce model given that two lines of data in the matrix are required to compute a single value for the power of the matrix. One of at least two strategies may be used to computing the power of the matrix (matrix square, M2) based on simplicity of execution or improved memory usage.

Abstract: To implement open information extraction, a new extraction paradigm has been developed in which a system makes a single data-driven pass over a corpus of text, extracting a large set of relational tuples without requiring any human input. Using training data, a Self-Supervised Learner employs a parser and heuristics to determine criteria that will be used by an extraction classifier (or other ranking model) for evaluating the trustworthiness of candidate tuples that have been extracted from the corpus of text, by applying heuristics to the corpus of text. The classifier retains tuples with a sufficiently high probability of being trustworthy. A redundancy-based assessor assigns a probability to each retained tuple to indicate a likelihood that the retained tuple is an actual instance of a relationship between a plurality of objects comprising the retained tuple. The retained tuples comprise an extraction graph that can be queried for information.

Abstract: There is provided an information processing apparatus including an information amount gain calculation unit that, on the assumption that a factor that could cause a state transition in a state transition model occurs and the state transition takes place as a result of an occurrence of the factor, determines an information amount gain, which is an information amount obtained by causing the factor to occur regarding a causal relationship between the factor and the state transition and observing a result thereof, an evaluation value calculation unit that determines an evaluation value to evaluate effectiveness of causing each of the factors to occur based on the information amount gain to acquire the causal relationship between the factor and the state transition, and a decision unit that decides the factor to be occurred based on the evaluation value.

Abstract: A system (1) comprises a physical surgical simulator (11) which transmits data concerning physical movement of training devices to an analysis engine (12). The engine (12) automatically generates rules for a rule base (13a) in a learning system (13). The learning system (13) also comprises content objects (13b) and 3D scenario objects (13c). A linked set of a 3D scenario object (13c), a rule base (13a), and a content object (13b) are together a lesson (10). Another simulator (14) is operated by a student. This transmits data concerning physical movement of training devices by a student to a verification engine (15). The verification engine (15) interfaces with the rule base (13a) to display the lesson in the manner defined by the lesson rule base (13a). It calculates performance measures defined in the lesson rule base (13a). It also records the performance measures into a lesson record (18) and it adapts the display of the lesson in line with the parameters defined in the lesson rule base (13a).

Abstract: A system and method for the dynamic allocation of resources based on fairness, throughput, and user behavior measurement. A resource allocation decision can be made based on an index value computed by a selection index function. A fairness coefficient and a throughput coefficient, which represent the significance of fairness and throughput can be computed utilizing a reinforcement learning algorithm. The degree of fairness and throughput coefficient can be varied while allocating resources. A user behavior coefficient with respect to a user can be computed to determine the degree of cooperativeness of the user with other users and the value of user behavior coefficient can be updated each time it interacts with the system.

Abstract: A method, system and computer program product for minimizing a rule set. A rule set application graph that describes a set of rules including actions and cases is built, whereby each rule defines an action for one or more cases. A rule violation graph for each rule describing the actions and cases not defined for that rule is built. A subset of rules having a reduced number of rules with the same set of actions and cases as the rule set application graph is determined by exploring candidate subsets of the rule set that are sufficient for reproducing the behavior of the original rule set.

Abstract: The method for implementing meta rules on an executable rule engine includes parsing a business rule as input into a meta rule on a rule engine. The meta rule includes a first expression defining one or more style conditions for business rules. The business rule includes a second expression defining logic for an entity. The method includes determining that a business rule violates a style condition defined by the meta rule. The business rule and the meta rule conform to a common business rule syntax. The method includes generating a notification in response to determining that the business rule violates the style condition of the meta rule.

Abstract: Systems and methods for classifying a set of documents are provided. In some aspects, a method includes receiving a subset of the set of documents. The method also includes automatically determining at least one classification rule for the subset of documents based on the documents in the subset. At least a true-positive threshold proportion of documents in the subset of documents follows the at least one classification rule. At most a false-positive threshold proportion of documents in the set of documents and not in the subset of documents follow the at least one classification rule. The method also includes storing the at least one classification rule in association with the subset of documents.

Abstract: Methods and systems for forecasting a future event in an event stream are provided herein. The event stream includes a number of events, wherein each of the events includes an event label and an associated time stamp. The system includes a processor that is adapted to execute stored instructions and a system memory. The system memory includes code configured to generate one or more decision graphs for predicting events with event labels chosen from a number of event labels based on the events within the event stream, wherein the decision graph includes decision nodes and leaf nodes, and wherein each of the decision nodes includes a question. The system memory also includes code configured to analyze event stream data using the decision graph and forecast a future event in the event stream based on the analysis of the event stream data.

Abstract: A system and method for declarative network access control are provided. The system includes an interpreter, a rules engine, a storage device, and a processor. The interpreter transforms sentences in a declarative network access control language to rules. The rules engine evaluates the rules to produce actions for providing access control to a network at a point of access. The storage device stores instructions for the interpreter, the rules and the rules engine and the processor executes those instructions.

Abstract: A computer-implemented method is provided for performing mishap risk assessment within a system. The method includes providing a first set of data including risk information associated with at least one hazard within the system, correlating all input first set of data with a second set of data defined as a plurality of mishaps of the system such that the hazard correlates with each mishap to assess mishap potential, storing the correlated first and second sets of data, and performing mishap risk assessment within the system based the correlated data including the first and second sets of data.

Abstract: This disclosure describes systems and methods for identifying and correcting anomalies in web graphs. A web graph is transformed into a set of weighted features. The set of weighted features are then transformed into a signature via a SimHash algorithm. The signature is compared to the signature of one or more other web graphs in order to determine similarity between web graphs. Actions are then carried out to remove anomalous web graphs and modify parameters governing web mapping in order to decrease the likelihood of future anomalous web graphs being built.

Abstract: Apparatus and method for assessing odors, comprises an electronic nose, to be applied to an odor and to output a structure identifying the odor; a neural network which maps an extracted structure to a first location on a pre-learned axis of odor pleasantness; and an output for outputting an assessment of an applied odor based on said first location. The assessment may be a prediction of how pleasant a user will consider the odor.

Abstract: Embodiments of systems and methods for automatic combination of text mining services, may comprise an instance generation component and an auto-mapping component. From common text sources, the instance generation component generates instances for taxonomy elements attached to a particular text mining service. These instances are then forwarded to the auto-mapping component, which computes a mapping between different taxonomies. This mapping may be saved to avoid repeated instance generation and mapping processes for similar taxonomies. The computed mapping may in turn be input to a result combiner element, together with extraction results from calling the different text mining services. The result combiner returns the merged result sets to the execution, and finally to the user or API.

Abstract: A method for improved, automated analysis of a data set improves the reliability of the data set by comparing the data set with a model of similar data. The method may be used in applications such as medical imaging, clinical trial participant selection, marketing, security, traffic control, and other applications.

Abstract: The aspects of the disclosed embodiments include clustering a set of discrete user interface states into groups; presenting the groups on a display of a device; and enabling selection of any state within a presented group, wherein selection of a state returns the user interface to the selected state.

Abstract: The present invention generally relates to a computerized system and method for creating, optimizing, and using a rules processing system that evaluates multiple rules against facts and events and detects, identifies, reacts to, and reports on events of interest. Events of interest may pertain to any subject matter, and in an embodiment, relate to securities (e.g., stocks, bonds, etc.) transactions. The system and method of the present invention also identifies patterns in large data sets using dynamically changing rules, and as a result, makes the processing and use of rules more efficient.

Abstract: Systems, methods, and devices are described for implementing learning algorithms on data sets. A data set may be partitioned into a plurality of data partitions that may be distributed to two or more processors, such as a graphics processing unit. The data partitions may be processed in parallel by each of the processors to determine local counts associated with the data partitions. The local counts may then be aggregated to form a global count that reflects the local counts for the data set. The partitioning may be performed by a data partition algorithm and the processing and the aggregating may be performed by a parallel collapsed Gibbs sampling (CGS) algorithm and/or a parallel collapsed variational Bayesian (CVB) algorithm. In addition, the CGS and/or the CVB algorithms may be associated with the data partition algorithm and may be parallelized to train a latent Dirichlet allocation model.