Abstract: A method for recommending an application includes obtaining an input model representing user interaction patterns during execution of a first application. The input model is compared to a reference model representing user interaction patterns during execution of a second application. A similarity is determined between the input model and the reference model. A recommendation of the second application is generated in response to the similarity.

Abstract: A sound mixture may be received that includes a plurality of sources. A model may be received for one of the source that includes a dictionary of spectral basis vectors corresponding to that one source. At least one feature of the one source in the sound mixture may be estimated based on the model. In some examples, the estimation may be constrained according to temporal data.

Abstract: A system and method for sharing information across security boundaries including a server for sharing information between networks. The method for includes receiving data structured as semantic statements, retrieving a set of rules and ontology, processing a semantic statement from data with rules and ontology, determining whether the semantic statement is consistent with rules and ontology, and determining a fact that gives rise to an inconsistency if the semantic statement is inconsistent. The method further includes removing the fact that gives rise to the inconsistency and releasing data when the semantic statement is consistent with rules and ontology.

Abstract: Paralinguistic indicators are translated at a paralinguistic translation server by receiving from a source a first set of data related to a first paralinguistic indicator that is configured to enable non-verbal communications between a source and a destination. The source is one of an instant messaging system and a virtual world system and the destination is one of the textual instant messaging system and a virtual world system but differs from the source. The first set of data related to the first paralinguistic indicator is translated into a second set of data related to a second paralinguistic indicator, such that the second paralinguistic indicator that is at least partially synonymous to the non-verbal communications associated with the first paralinguistic indicator. The second set of data related to the second paralinguistic indicator is transmitted to the destination.

Abstract: A cache management system and method and a content distribution system. In one embodiment, the cache management system includes: (1) a content request receiver configured to receive content requests, (2) a popularity lifetime prediction modeler coupled to the content request receiver and configured to generate popularity lifetime prediction models for content that can be cached based on at least some of the content requests, (3) a database coupled to the popularity lifetime prediction modeler and configured to contain the popularity lifetime prediction models and (4) a popularity lifetime prediction model matcher coupled to the content request receiver and the database and configured to match at least one content request to the popularity lifetime prediction models and control a cache based thereon.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for rule-based binding. In one aspect, a method includes receiving first input to a graphical user interface (GUI) associating a property of a data model presented in the GUI with a data view component of a document presented in the GUI, wherein a change to a value of the data view component is reflected in a value of the property in the data model when the document is used in a workflow, and wherein the workflow is a logical sequence of documents, including the document, that is processed according to the logical sequence such that values for one or more data view components associated with the documents are received.

Abstract: One or more systems and methods for knowledge pattern search from networked agents are disclosed in various embodiments of the invention. A system and a related method can utilizes a knowledge pattern discovery process, which involves analyzing historical data, contextualizing, conceptualizing, clustering, and modeling of data to pattern and discover information of interest. This process may involve constructing a pattern-identifying model using a computer system by applying a context-concept-cluster (CCC) data analysis method, and visualizing that information using a computer system interface. In one embodiment of the invention, once the pattern-identifying model is constructed, the real-time data can be gathered using multiple learning agent devices, and then analyzed by the pattern-identifying model to identify various patterns for gains analysis and derivation of an anomalousness score.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving a plurality of first training examples, training a first predictive model using the first training examples, for each example in the first training examples, providing the first features of the example to the trained first predictive model to generate a respective first prediction, generating a second training example for each of the first training examples, wherein the second training example comprises the first features of the first training example and an answer that indicates whether the first answer of the first training example matches the respective first prediction of the first training example, training a second predictive model using the second training examples, and using the trained second predictive model to determine a confidence score for a prediction generated by the trained first predictive model.

Abstract: Embodiments of the invention provide a neural core circuit comprising a synaptic interconnect network including plural electronic synapses for interconnecting one or more source electronic neurons with one or more target electronic neurons. The interconnect network further includes multiple axon paths and multiple dendrite paths. Each synapse is at a cross-point junction of the interconnect network between a dendrite path and an axon path. The core circuit further comprises a routing module maintaining routing information. The routing module routes output from a source electronic neuron to one or more selected axon paths. Each synapse provides a configurable level of signal conduction from an axon path of a source electronic neuron to a dendrite path of a target electronic neuron.

Abstract: To entities that are likely to engage in a behavior, a behavior discrimination threshold for each of a plurality of behavior variables is determined. Variable values for each entity of a plurality of target entities and for each of the behavior variables are compared to the relevant behavior discrimination threshold to provide identifying variables for each entity. An index value is determined for each of the plurality of target entities based on the identifying variables for that entity. An index threshold is determined such that those entities of the target entities having index values that meet or exceed the index threshold are likely to exhibit or engage in the behavior more frequently than a random sampling of the plurality of training entities. Actions designed to affect the likelihood that the resulting targeted entities will engage in the behavior may be directed to the targeted entities.

Abstract: A system is disclosed for evaluating communicative acts to determine a social regard score between two communicating entities participating in the communicative act. The two communicating entities collectively define a communication pair. The system includes a patterns database and an etiquette processor. The patterns database stores behavior recognition patterns defining particular redressive behaviors that may be used in the communicative acts and a redress score associated with each one of the particular redressive behaviors. The etiquette processor is in communication with the patterns database and is configured to determine a pairwise regard score for the communicative pair based on ones of the particular redressive behaviors identified in the communicative acts between the two communicating entities of the communicative pair.

Abstract: A method of selecting and presenting content on a first system based on user preferences learned on a second system is provided. The method includes receiving a user's input for identifying items of the second content system and, in response thereto, presenting a subset of items of the second content system and receiving the user's selection actions thereof. The method includes analyzing the selected items to learn the user's content preferences for the content of the second content system and determining a relationship between the content of the first and second content systems to determine preferences relevant to items of the first content system. The method includes, in response subsequent user input for items of the first content system, selecting and ordering a collection of items of the first content system based on the user's learned content preferences determined to be relevant to the items of the first content system.

Abstract: How much is the net benefit of treating an individual: cost-effective, very small, or even negative? To address this question, a methodology for developing an incremental effect model based on randomized test data is provided. The concept of an incremental effect area index is introduced for measuring the model's quality. A new variable screening technique is proposed to identify variables that are decision relevant and preferably time invariant. A piecewise linear function is created for each continuous variable to approximate the relationship between the incremental effect and the variable, based on a binning technique. Finally, a score is created as the weighted sum of a set of functions, with each function being the empirical prediction of the incremental effect based on a variable, wherein weights are chosen to maximize the incremental effect area index. The methodology creates an improved incremental effect model, leading to more cost-effective strategies in business practice.

Abstract: Exemplary methods and systems are disclosed that apply feedback-based machine learning in order to more intelligently use context information to automate certain actions. An exemplary method involves: determining a first context based on a combination of two or more context signals, using a context-to-action mapping to determine a first action that corresponds to the first context, initiating the first action, after initiating the first action, receiving a data signal corresponding to a user-action, analyzing the data signal to determine a feedback relationship between the user-action and the first action, and based at least in part on the feedback relationship, updating the context-to-action mapping.

Abstract: Some embodiments of this disclosure relate to techniques for determining trustworthiness scores for entities in an online environment. Often, the techniques gather behavioral information regarding entities from a number of different online sources, and then process this information to generate the trustworthiness scores. In some embodiments, a portion of one entity's score can be scaled with regards to a corresponding portion of another entity's score. In still other embodiments, an entity can be provided with a trustworthiness score that has different category components.

Abstract: A computer-implemented method for generating a threat classifier is described. A parameter collection module is distributed to a plurality of client processing systems. The module comprises a set of rules to detect a behavior in the client processing systems. If one or more of the set of rules are satisfied, input data indicative of a plurality of client processing parameters is received. The input data is scaled to provide a plurality of parameter vectors. Each of the parameter vectors are classified as a threat or a non-threat. A machine learning process is performed on at least one of the classified parameter vectors. The threat classifier is generated from the machine learning process. The threat classifier is transferred to at least one client processing system. The threat classifier is configured to automatically determine if a process to be performed in a client processing system is malicious.

Abstract: A method, apparatus and computer program product for performing probabilistic inference and providing related solution methods is presented. At least one state space (SS) is obtained for variables of interest relating to a problem of interest. None or more densities (D) defining pure functions over locations in the at least one SS are also obtained as is none or more kernels (K) defining a stochastic walk through the at least one SS. A virtual machine executes a stochastic walk through the state space to produce a solution for a problem of interest.

Abstract: A Markov decision process-based support tool for reservoir development planning can comprise a source of input data, an optimization model, a high fidelity model for simulating the reservoir, and one or more solution routines interfacing with the optimization model. The optimization model can consider unknown parameters having uncertainties directly within the optimization model. The model incorporates the flexibility that a decision-maker has in the real world and allows the decision-maker to adjust the decisions based on new information. The model can systematically address uncertain data, for example comprehensively or even taking all uncertain data into account. Accordingly, the optimization model can provide flexible or robust solutions that remain feasible over an uncertainty space. Once the reservoir model is optimized, final development plans may be generated.

Abstract: This method for automatic analysis of failure or state messages generated by at least one complex system is characterized in that it comprises the steps for integrating said messages to a database of failure or state messages, and for determining with a computer, for each of said messages, an index of overall interest characterizing a degree of relevance of said message, on the basis of at least one parameter representative of a frequency of occurrence of similar messages in said database, and a correlation between said or each representative parameter and a predefined number of indexes of overall interest. A corresponding analysis system is also provided.

Abstract: A stochastic programming-based decision support tool for reservoir development planning can comprise a source of input data, an optimization model, a high fidelity model for simulating the reservoir, and one or more solution routines interfacing with the optimization model. The optimization model can consider unknown parameters having uncertainties directly within the optimization model. The model incorporates the flexibility that a decision-maker has in the real world and allows the decision-maker to adjust the decisions based on new information. The model can systematically address uncertain data, for example comprehensively or even taking all uncertain data into account. Accordingly, the optimization model can provide flexible or robust solutions that remain feasible over an uncertainty space. Once the reservoir model is optimized, final development plans may be generated.