Abstract: Some embodiments are directed to generating a first probability value that represents a percentage of times that first bit values for a given bit position of a first plurality of candidate solutions equate to a pre-defined number, where the first plurality of candidate solutions has converged on a sub-optimal solution during a simulation of an optimization problem using an optimization algorithm. Some embodiments are further directed to generating a second probability value that is inversely biased from the first probability value; and generating a second plurality of candidate solutions with the second probability value, where the second plurality of candidate solutions are inversely biased from the first bit values for the given bit position.

Abstract: The parking availability for a geographic area is predicted using a parking availability model. The geographic population density for the geographic area is first predicted. The predicted geographic population density is then applied to the parking availability model to produce a prediction of the parking availability for the geographic area. The parking availability model comprises a function that relates predicted geographic population densities with parking availabilities for a geographic area. The predicted parking availability for the geographic area is stored in a computer-readable storage medium. The parking availability predictions may be displayed as a layer within a map, and may be produced for a specifically requested geographic area, or a general geographic area.

Abstract: An apparatus operating on a time sequence of events includes an event handling module configured to generate a predicted label for a current observed event of the time sequence of events and a true label handling module configured to process a true label revealed for an observed event of the time sequence of events. The event handling module and the true label handling module cooperatively model stochastic dependence of a true label for the current observed event based on the time sequence of events and revealed true labels for the past observed events of the time sequence of events. The event handling module and the true label handing module operate asynchronously. The event handling module and the true response handling module suitably operate as one or more digital processors.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining query suggestions from multiple correlation measures. In one aspect, a method includes receiving a first query and second queries, each of the first and second queries including one or more terms; for each second query and a linear model, receiving correlation scores measuring the correlation between the first query and the respective second query, each correlation score received from a respective correlation process, and each respective correlation process being different from the other respective correlation processes, and applying the linear model to the plurality of correlation scores to determine a combined correlation score that quantifies a combined correlation between the first query and the respective second query based on the plurality of correlation scores. The second queries are ranked in an order according to their respective combined correlations scores.

Abstract: An example system and method where some operations include determining constraint compliant values for each of a set of constrained variables of an optimization problem. The constraint compliant values comply with a constraint condition for the optimization problem. The operations can further include generating a population of constraint compliant candidate solutions for a computer-based simulation that implements a population-based optimization algorithm for the optimization problem. The candidate solutions use a subset of the constraint compliant values such that each of the candidate solutions comply with the constraint condition.

Abstract: An example system and process where some operations include determining variables of an optimization problem, which include one or more constrained variables (“constrained variables”) constrained by one or more constraint conditions for the optimization problem and one or more non-constrained variables (“non-constrained variables”). The operations further include determining values for the constrained variables that comply with the one or more constraint conditions (“constraint compliant values”) and generating values for the non-constrained variables (“non-constrained values”). The operations further include, prior to running a computer based simulation that implements a population-based optimization algorithm, randomly combining ones of the constraint compliant values with ones of the non-constrained values into candidate solutions, where each of the candidate solutions includes at least one of the constraint compliant values to satisfy the one or more constraint conditions.

Abstract: An example system and process with operations that include determining, for constrained variables of an optimization problem, compliant values that comply with a constraint condition that mutually constrains the constrained variables. The operations further include generating a population of candidate solutions for the optimization problem. The candidate solutions use a subset of the compliant values such that each of the candidate solutions comply with the constraint condition. The operations further include, while running a computer-based simulation with the population of candidate solutions, determining that a mutated candidate solution, created from mutating one of the candidate solutions, fails to comply with the constraint condition.

Abstract: The present disclosure provides novel techniques for defining empirical models having control, prediction, and optimization modalities. The empirical models may include neural networks and support vector machines. The empirical models may include asymptotic analysis as part of the model definition as allow the models to achieve enhanced results, including enhanced high-order behaviors. The high-order behaviors may exhibit gains that are non-zero trending, which may be useful for controller modalities.

Abstract: Disclosed is a tool that assesses and classifies data in a data set to and compares those assessments with nominal attributes and text attributes of data present in a new record to assign a classification to the new record. The classification assigned to the new record is provided a confidence level based on both a qualitative factor and a quantitative factor. The qualitative factor may be calculated by forming of a list of important words for each class and comparing the list to data in the new record and converting the comparison into a confidence level; the quantitative factor may be calculated by estimating the importance or weight of several factors, ratios of certain probabilities related to the most likely class and to the second most likely class, and using the importance of the factors and matchfactors to scale the resulting ratio, then transforming the resulting ratio into a confidence level.

Abstract: Some embodiments of a method to support multi-result set calculation in a rule engine have been presented. A rule engine can compile a set of rules to build a network for evaluating facts against the rules. The rules include at least one rule requiring multiple calculations to be executed for the same set of facts. The rule engine can create a single multi-result set calculation node for this rule in the network. The multi-result set calculation node can generate a set of results and add the set of results to a tuple to be propagated to a second node connected to an output of the multi-result set calculation node.

Abstract: Embodiments of the invention collect data or information from a dynamic and adaptive target group selection. Sets of experts are selected that each have higher value metrics scores relative to scores of other, unselected experts of a population of known experts, and wherein the metric values are indicative of an expertise relevant to one or more questions in a survey. Responses to the survey are used to expand the set of experts by adding experts noted in answer referrals, and to automatically update the expert value metric scores as a function of response timeliness and of degrees of correlation of answers to an expected answer or other norm. The survey is updated by removing satisfied questions, and expert selections, answers analysis and survey updating and resending steps are iteratively repeated until each question is satisfied, wherein the expert sets are dynamically revised for each iteration.

Abstract: A codebook generating method includes a dividing and transforming step dividing an original image into original blocks and transforming the original blocks into original vectors; a dividing step grouping the original vectors to obtain centroids; a first layer neuron training step selecting a portion of the centroids as first-level neurons; a grouping step assigning each of the original vectors to a closest first-level neuron so as to obtain groups; a second layer neuron assigning step assigning a number of second-level neurons in each of the groups, and selecting a portion of the original vectors in each of the groups as the second-level neurons; and a second layer neuron training step defining the original vectors in each of the groups as samples, training the second-level neurons in each of the groups to obtain final neurons, and storing vectors corresponding to the final neurons in a codebook.

Abstract: Methods, systems, and techniques for generating sentiment data are provided. Example embodiments provide a Sentiment Thesaurus Framework (STF), which provides a sentiment vocabulary meeting a set of criteria and a sentiment thesaurus according to certain connectedness rules. In one embodiment, the STF provides the sentiment thesaurus by relating connected adjective word-senses to valid sentiment adjective word-senses. The degree of connectedness is limited to one shift in meaning from one adjective to another, which implies at most two non-satellite or axle adjectives between a valid sentiment and a related adjective word-sense.

Abstract: A method, system, and computer program product are provided for process automation. The method includes: monitoring one or more workstations including monitoring screen contents and user actions at the workstation; and analysing the screen contents and user actions into monitored functional events. The method further includes: providing multiple focal states as defined sequences of functional events with one or more facilitating scripts associated with a focal state, wherein a facilitating script provides one or more automatic actions; and matching a sequence of monitored functional events to a defined sequence of functional events of a focal state. The one or more automatic actions of a facilitating script associated with the matched focal state are then applied.

Abstract: Embodiments are directed towards clustering cookies for identifying unique mobile devices for associating activities over a network with a given mobile device. The cookies are clustered based on a Bayes Factor similarity model that is trained from cookie features of known mobile devices. The clusters may be used to determine the number of unique mobile devices that access a website. The clusters may also be used to provide targeted content to each unique mobile device.