Abstract: The machine learning apparatus includes: a state data observing unit which observes state data of the laser apparatus, including data output from a reflected light detecting unit for measuring a reflected light amount; an operation result acquiring unit which acquires a success/failure result indicating whether the machining has been started successfully by the laser beam output from a laser oscillator; a learning unit which learns light output command data by associating the light output command data with the state data of the laser apparatus and the success/failure result of the machining start; and a decision making unit which determines the light output command data by referring to the light output command data learned by the learning unit.

Abstract: An integrated and comprehensive method and system is disclosed for management and optimization of innovation and associated processes under uncertainty. A first embodiment of the invention consists of a data mining and clustering module to compare a new innovation submission with existing internal and external entries and databases, identify similarities and group similar entries together. A second embodiment of the invention is directed towards an intelligent machine learning module to learn from the available data of previous innovation projects and provide estimates of outputs or target values for new innovation submissions or entries. In a third embodiment of the invention, an uncertainty quantification method and system is introduced to handle uncertain inputs of innovation entries and provide probabilistic estimates of outputs by generating a plurality of solutions and scenarios.

Abstract: Techniques related to implementing neural networks for speech recognition systems are discussed. Such techniques may include processing a node of the neural network by determining a score for the node as a product of weights and inputs such that the weights are fixed point integer values, applying a correction to the score based a correction value associated with at least one of the weights, and generating an output from the node based on the corrected score.

Abstract: A machine learning problem assessment system that identifies potential machine learning problems in a machine learning system in which learning code evaluates data to correlate estimated learned data with data patterns. An accessing component accesses the learning code and/or the data that the learning code evaluates. A problem identifies component estimates, based on the accessed code and/or data, that there is a potential problem with machine learning system. A rectification component at least partially automatically rectifies the identified potential problem with the machine learning system by performing a computerized action on the machine learning system. The identified potential problem may affect quality (e.g., appropriateness of conclusions) and/or performance (e.g., speed) of the learning of the machine learning system.

Abstract: A method for measuring a technical system, especially a combustion engine for a motor vehicle, using a number of measuring points to in each instance obtain a value of at least one output variable. The method includes selecting a measuring point from a quantity of measuring points, determining a confidence value for the selected measuring point on the basis of a classification model, the confidence value indicating a permissibility of an operating point that results owing to the operation of the technical system at the measuring point, measuring the technical system at the selected measuring point as a function of the confidence value, and updating the classification model, with an indication as to whether the operating point of the technical system set by the measurement of the selected measuring point is permissible.

Abstract: An input time-series is decomposed into a set of constituent frequencies. For each constituent frequency in a subset of the set of constituent frequencies, a corresponding forecasting model is selected in a subset from a set of forecasting models. From a set of component forecasts produced by the subset of forecasting models, a subset of component forecasts is selected. A component forecast in the subset of component forecasts is selected according to a component forecast selection condition. The subset of component forecasts is output to revise the forecast selection condition. A revised forecast selection condition increases a relevance of a future subset of component forecasts.

Abstract: Systems, methods, and non-transitory computer-readable media can collect past user information and churn data for a plurality of users. A churn prediction model is trained using the past user information and churn data. A churn propensity score is calculated for a present user based on the churn prediction model, the churn propensity score indicative of the likelihood of the present user to churn.

Abstract: A system, a machine-readable storage medium storing instructions, and a computer-implemented method are described herein to a Discussion Relevance Engine that filters a plurality of discussions in a social network to identify a discussion pool. The Discussion Relevance Engine identifies a plurality of eligible discussions in the discussion pool, wherein each eligible discussion corresponds to a respective social network member group to which a target member account has previously subscribed. The Discussion Relevance Engine calculates, for each eligible discussion, a relevance score predictive of a relevance of the eligible discussion to the target member account. The Discussion Relevance Engine recommends at least one of the eligible discussions to the target member account based at least in part on the calculated relevance scores.

Abstract: A system, a machine-readable storage medium storing instructions, and a computer-implemented method are described herein to a Group Relevance Engine that generates, for a group in a social network, an aggregate group feature based on a common attribute shared amongst member accounts currently subscribed to the group. The Group Relevance Engine identifies an account feature corresponding to the common attribute in a profile of a target member account. The Group Relevance calculates a relevance score based at least on a match between the aggregate group feature and the account feature. The Group Relevance determines whether to recommend the group to the target member account based at least on the relevance score.

Abstract: Embodiments of the invention relate to identification of material that contains linguistically related content. Key phrases are filtered through a content store to ascertain the linguistically related content and to move the identified content to a target corpus. At least two iterations of the filtering process are employed. Each subsequent iteration of the filtering process identifies at least one new key phrase within the filtered material. In addition, each subsequent iteration takes place with a union of each previously employed key phrase and each new key phrase. As new content is identified, the content is populated to the target corpus.

Abstract: A causal relationship is represented with a data structure including target identification information for identifying a target, index identification information of each of indexes to be used for quantitatively describing an event that occurs to the target, and causal relationship information for each pair of two indexes selected from the indexes. The causal relationship information includes direction information representing which one of the two indexes is a cause index and which one is an effect index, strength information representing a causal strength between the cause index and the effect index, time information representing a delay time for propagation of an influence of the cause index to the effect index, and correlation information representing a direction of change in the effect index with respect to an increase or decrease in the cause index.

Abstract: Embodiments of the present invention are directed to facilitating concurrent forecasting associating with multiple time series data sets. In accordance with aspects of the present disclosure, a request to perform a predictive analysis in association with multiple time series data sets is received. Thereafter, the request is parsed to identify each of the time series data sets to use in predictive analysis. For each time series data set, an object is initiated to perform the predictive analysis for the corresponding time series data set. Generally, the predictive analysis predicts expected outcomes based on the corresponding time series data set. Each object is concurrently executed to generate expected outcomes associated with the corresponding time series data set, and the expected outcomes associated with each of the corresponding time series data sets are provided for display.

Abstract: A multi-horizon predictor system that predicts a future parameter value for multiple horizons based on time-series data of the parameter, external data, and machine-learning. For a given time horizon, a time series data splitter splits the time into training data corresponding to a training time period, and a validation time period corresponding to a validation time period between the training time period and the given horizon. A model tuner tunes the prediction model of the given horizon fitting an initial prediction model to the parameter using the training data thereby using machine learning. The model tuner also tunes the initial prediction model by adjusting an effect of the external data on the prediction to generate a final prediction model for the given horizon using the validation data. A multi-horizon predictor causes the time series data splitter and the model tuner to operate for each of multiple horizons.

Abstract: A method of maintaining interoperability amongst Internet of Things (IoT) devices connected via an IoT integration platform is disclosed. The method includes: receiving a selection of a semantic label associated with an IoT device; determining a recommendation of an interoperable rule based on the semantic label, the interoperable rule having a condition trigger and an action policy for execution at satisfaction of the condition trigger; presenting the recommendation on a rule management interface; and receiving a confirmation from a user through the rule management interface to activate the interoperable rule.

Abstract: In at least one embodiment, a method and a system for determining a set of plans that best match a set of preferences. The method may include receiving into a goal specification interface at least one goal to be accomplished by the set of plans; receiving into a preference engine a pattern that includes preferences; generating a planning problem by using the preference engine; generating a set of plans by at least one planner; and providing the set of plans for selection of one plan to deploy. In a further embodiment, the preferences may be an occurrence or non-occurrence of at least one component, an occurrence of one component over another component, an ordering between at least two components, an existence or non-existence of at least one tag in a final stream, an existence of one tag over another tag in the final stream.

Abstract: Predicting program performance on hardware devices, in one aspect, may comprise obtaining a set of existing applications and observed performance on a target hardware device. The set of existing applications are run on one or more general purpose computer processors and application features are extracted from the existing application. A machine learning technique is employed to train a predictive model based on the extracted application features and the observed performance for predicting application performance on the target hardware device.

Abstract: Disclosed is a computer-implemented method for generating a user interface to a data analysis engine comprising a plurality of analysis tools. The method comprises providing a methods knowledge base comprising rules which map data types and/or analysis goals to analysis tools; an inference engine; and a user interface module.

Abstract: A method, procedure and algorithm are provided for efficient resource provisioning in Hadoop MapReduce. The crux of the method, procedure and algorithm is not tied to any specific system, and can be applied to many processes and devices. It provides a general approach and techniques based on an algorithm with mathematical formulas to find the Best Trade-off Point on an elbow curve, non-inverted or inverted, of performance vs. resources. It is applicable to any systems relying on a trade-off elbow curve for making good decision.

Abstract: A pseudo-relevance feedback (PRF) system is disclosed that determines an optimized relevance model for a search query by utilizing a posterior relevance model to estimate the likelihood that an initial set of top-K retrieved documents would be retrieved given the posterior relevance model, re-ranking the top-K documents based on their respective estimates of likelihood of retrieval, determining a rank similarity between the initial ranking of the top-K documents and the re-ranking of the top-K documents, updating one or more model parameters of the posterior relevance model based on the rank similarity, and iteratively performing the above process until the rank similarity is maximized, at which point, the optimized relevance model is obtained.

Abstract: A centralized computer system estimates a failure probability to print a 3D model by analyzing the 3D model to identify certain predetermined features and receive an indication of print failure. Based on correlated analyses and indications of success or failure received by a sample of users printing various 3D models having different combinations of features, the centralized computer system produces and maintains a data structure of features and success rates. Subsequently, the centralized computer system may receive a 3D model analysis, compare the 3D model analysis to the data structure to determine an estimated success probability, and report the estimated success probability to the user that submitted the 3D model.

Abstract: Methods, system, and apparatus for pre-computing data metrics. A method can include receiving, by one or more computers, (i) data from a user including a plurality of data metrics, and (ii) historical data associated with the user; generating, by the one or more computers and based at least on the historical data associated with the user, a forecast for the user using an artificial neural network, the forecast indicating a prediction of future user behaviors; determining, by the one or more computers and based at least on the forecast for the user, a subset of data metrics, from among the plurality of data metrics, that are likely to be used by the user; performing, by the one or more computers, one or more automatic data operations on the subset of data metrics; and providing, by the one or more computers, the processed subset of data metrics for output.

Abstract: A Probabilistic Quantum Circuit with Fallback (PQFs) is composed as a series of circuit stages that are selected to implement a target unitary. A final stage is conditioned on unsuccessful results of all the preceding stages as indicated by measurement of one or more ancillary qubits. This final stage executes a fallback circuit that enforces deterministic execution of the target unitary at a relatively high cost (mitigated by very low probability of the fallback). Specific instances of general PQF synthesis method and are disclosed with reference to the specific Clifford+T, Clifford+V and Clifford+?/12 bases. The resulting circuits have expected cost in logb(1/?(log(log(1/?)))+const wherein b is specific to each basis. The three specific instances of the synthesis have polynomial compilation time guarantees.

Abstract: The present teaching relates to distributed deep machine learning on a cluster. In one example, a request is received for estimating one or more parameters associated with a machine learning model on a cluster including a plurality of nodes. A set of data is obtained to be used for estimating the one or more parameters. The set of data is divided into a plurality of sub-sets of data, each of which corresponds to one of the plurality of nodes. Each sub-set of data is allocated to a corresponding node for estimating values of the one or more parameters based on the sub-set of data. Estimated values of the one or more parameters obtained based on a corresponding sub-set of data allocated to the node, are received from each of the plurality of nodes. The one or more parameters of the machine learning model are estimated based on the estimated values of the one or more parameters generated by at least some of the plurality of nodes.

Abstract: A method, computer program product and computer system are provided. A processor identifies a plurality of numeric expressions in a text corpus associated with a type of item. A processor generates a plurality of feature vectors corresponding to the identified plurality of numeric expressions. A processor identifies one or more common features of the plurality of feature vectors. A processor generates one or more rules for representing numeric quantities of the type of item based, at least in part, on the one or more common features of the plurality of feature vectors.

Abstract: Training instances from a target domain are represented by feature vectors storing values for a set of features, and are labeled by labels from a set of labels. Both a noise marginalizing transform and a weighting of one or more source domain classifiers are simultaneously learned by minimizing the expectation of a loss function that is dependent on the feature vectors corrupted with noise represented by a noise probability density function, the labels, and the one or more source domain classifiers operating on the feature vectors corrupted with the noise. An input instance from the target domain is labeled with a label from the set of labels by operations including applying the learned noise marginalizing transform to an input feature vector representing the input instance and applying the one or more source domain classifiers weighted by the learned weighting to the input feature vector representing the input instance.

Abstract: A method and systems for intelligent selection and classification of oracles used to train a predictive cognitive system. A computerized oracle-selection system identifies candidate “oracle” experts in a field of endeavor known as a domain. The system retrieves contemporaneous natural-language “artifact” documents that each refer to or were produced by an oracle, and contains information from which may be predicted a future event related to the domain. The system assigns each oracle a confidence factor that identifies the accuracy of that oracle's predictions, and ranks the artifacts by how closely each matches the domain and by the confidence factors of its associated oracles. The artifacts are merged into the corpus, where the rankings indicate which artifacts may most reliably be used by the cognitive system to formulate predictive responses to user queries. This procedure is repeated each time the system receives user feedback or an updated set of artifacts.

Abstract: A method, computer program product and computer system are provided. A processor identifies a plurality of numeric expressions in a text corpus associated with a type of item. A processor generates a plurality of feature vectors corresponding to the identified plurality of numeric expressions. A processor identifies one or more common features of the plurality of feature vectors. A processor generates one or more rules for representing numeric quantities of the type of item based, at least in part, on the one or more common features of the plurality of feature vectors.

Abstract: Embodiments of the present invention disclose system to determine the best model to perform lead scoring for a given data set. The system can perform a multi-step iterative procedure including variable selection, feature set selection, training data selection, model development, model validation and process optimization. The system also performs local and global optimizations iteratively to determine the best possible model for a given scenario.

Abstract: Disclosed in some examples are systems, methods, and machine readable mediums which allow for the automatic creation of a skills hierarchy. The skills hierarchy comprises an organization of a standardized list of skills into a hierarchy that describes category relationships between the skills in the hierarchy. The category relationships may include no relationships, parent relationships, and child relationships. A skill may be considered a parent of another skill if the parent skill describes a broader category of skill that includes the child. Other relationships such as grandparent (e.g., a parent's parent), great-grandparent, grandchild, great grandchild and so on may be defined inferentially as well. In some examples, the constructed hierarchy may be organized with broader skills at higher levels and narrower skills at lower levels.

Abstract: Method and systems are disclosed for training state-classifiers for classification of cognitive state. A set of multimodal signals indicating physiological responses of an operator are sampled over a time period. A depiction of operation by the operator during the time period is displayed. In response to user input selecting a cognitive state for a portion of the time period, the one or more state-classifiers are trained. In training the state-classifiers, the set of multimodal signals sampled in the portion of the time period are used as input to the one or more state-classifiers and the selected one of the set of cognitive states is used as a target result to be indicated by the one or more state-classifiers.

Abstract: A method for optimizing seating capacity at a business establishment using a data processing system. Patrons of the establishment can request reservations using a computing device. Once the request has been made, the system determines whether one or more floor plan configurations have an available table capable of satisfying the request and reservation requirements. If the request can be satisfied, the reservation is confirmed and the table is assigned within the selected floor plan configuration and recorded within the reservation requirements. Walk-in patrons may also request a table. The system will produce floor plan configurations having an available table to accommodate the request in accordance with reservation requirements and business information. Business information includes data received from table activity, kitchen activity, and server activity, as well as patron requirements. The system can also predict a patron's wait time based on floor plan configuration and business information.

Abstract: A ticketing method for issuing a service ticket of a transport system to a passenger comprises: checking-in the passenger via a mobile device of the passenger upon accessing a vehicle of the transport system; checking-out the passenger via the mobile device upon exiting a vehicle of the transport system; and a server computer automatically calculating a price for a travel of the passenger within the transport system by evaluating check-in data representing the checking-in of the passenger and check-out data representing the checking-out of the passenger.

Abstract: The disclosure includes a method for booking latent inventory of a business, such as a spa business. Some methods can include determining, via a processing system, that a first unit of latent inventory is available at a first spa business. Methods can also include receiving, via the processing system, a first booking request from a customer to book the first unit of latent inventory. Some methods can include booking, via the processing system, the first unit of latent inventory with the first spa business. In some embodiments, the determining step is performed on a calendar day, and wherein the first unit of latent inventory is available on the calendar day. In response to booking the first unit of latent inventory a massage table can become available to use.

Abstract: This invention discloses a novel system and method for distributing electronic ticketing such that the ticket is verified at the entrance to venues by means of an animation or other human perceptible verifying visual object that is selected by the venue for the specific event. Tins removes the need to use a bar-code scanner on an LCD display of a cell phone or other device and speeds up the rate at which human ticket takers can verify ticket holders.

Abstract: A system and method is disclosed that enables the display of permits and/or permit information related to a specific location, collection of permitting data onsite, comparison of the onsite data to permitted constraints, and reporting the results of the inspection (as required under the appropriate regulatory policy or as requested by the organization or entity being inspected), as well as sending immediate notifications, as appropriate, to decision makers. In certain embodiments, the system and method may also offer predictions on the likelihood of an enforcement action against the organization given factors such as, but not limited to, the type of violation, degree of violation, and enforcement actions against others for similar violations. In other embodiments, the system and method allows the permittee to mitigate the risk of a violation by notifying emergency personnel in addition to decision makers within the organization.

Abstract: Business delivers product/s or service/s to customer using live location provided by customer's wireless device's live location which is shared by customer with the business. At the same time the business is sharing the delivery person's wireless device's live location with the customer. This enables self-discovery of the delivery person and the customer hence delivering the product/service to the customer.

Abstract: Aspects of the present disclosure provide a mechanism to directly interact and access with micro-services and/or services using natural-language and machine intelligence and algorithmic learning so that users may access desired micro-services and/or services with minimal interaction.

Abstract: Real time security, integrity, and reliability postures of operational (OT), information (IT), and security (ST) systems, as well as slower changing security and operational blueprint, policies, processes, and rules governing the enterprise security and business risk management process, dynamically evolve and adapt to domain, context, and situational awareness, as well as the controls implemented across the operational and information systems that are controlled. Embodiments of the invention are systematized and pervasively applied across interconnected, interdependent, and diverse operational, information, and security systems to mitigate system-wide business risk, to improve efficiency and effectiveness of business processes and to enhance security control which conventional perimeter, network, or host based control and protection schemes cannot successfully perform.

Abstract: Embodiments of the present invention relate to techniques for creating policies. A plurality of objects representative of semantic objects are provided to a user. An arrangement of a subset of the objects, the arrangement representative of a policy, is received. The arrangement is converted to instructions for implementation by an application configured to implement policies. One or more of the objects may include fields and/or controls for specifying criteria of semantic objects represented by the objects.

Abstract: Various embodiments herein provide a customized market platform for facilitating on-demand transport and delivery services for customers and service providers. The method supported by computing systems comprises generating matrixes of service request specific preferences and limitations preset by customers and service providers respectively to search for best matching service providers to perform the requested services with the assistance of various sets of indicators and search parameters. The platform provides panels for negotiating service request prices and optional bi-directional evaluation of customers and service providers by adding to either “favorites lists” or “blacklists.” The database incorporated with the platform will be dynamically updated to indicate changes by service providers and customers in their favorites lists, blacklists, preferences, limitations, and indicators.

Abstract: The technology described herein relates to frameworks and methodologies configured to provide organised activity management functionalities. Embodiments of the invention have been particularly developed primarily to assist in managing risk and compliance issues for organised activities where an organiser owes a duty of care towards participants, for example school excursions. While some embodiments will be described herein with particular reference to that application, it will be appreciated that the invention is not limited to such a field of use, and is applicable in broader contexts.

Abstract: Aspects of the subject disclosure may include, for example, a communication system that receive location data associated with mobile devices over a time period and evaluates the location data to predict hours of operation of an enterprise. The communication system operates by: selecting a first group of mobile devices based on geographical proximity to the enterprise; analyzing the location data to identify a subset of the first group predicted to correspond to employees of the enterprise; selecting a second group of the mobile devices by filtering the subset from the first group; analyzing the location data corresponding to the second group over the period of time to determine aggregate time periods when the second group are in the geographical proximity to the enterprise; and predicting the hours of operation of the enterprise according to the aggregate time periods. Other embodiments are disclosed.

Abstract: The present disclosure provides for a system, method and process for product authentication, product tracking for use with products intended to be introduced for circulation into the Supply chain; including machine and human readable product identification data; comprising a product data storage and look up means, for general consumers or Supply chain intermediaries, wherein the UPIT is affixed to the product or embedded onto the product label and is arranged for inspection by a human or at least one reading device, remote from the product data storage means and at least one point in the product supply chain; wherein the human data entry lookup or at least one reading device is arranged to verify the authenticity of the machine readable product identification data and thereby verifying the authenticity of the product itself based on the last transaction of the product in the supply chain.

Abstract: Convenience when a customer obtains merchandise is improved together with reduction in a delivery cost of the merchandise. There is provided a storage unit that holds storage area information on positions of plural storage areas and user information on action characteristics of plural users; a storage area extraction unit that extracts plural storage areas available for the respective users on the basis of the action characteristics of the plurality of users and the plurality of storage areas; a placement position determination unit that determines a storage area in which merchandise predicted to be purchased by each of the users is placed from the plurality of storage areas available for the respective users; and a delivery instruction creation unit that creates and transmits an instruction for delivering the merchandise predicted to be purchased by each of the users to the storage area determined by the placement position determination unit.

Abstract: A social networking-based web analytics data processing system having subject matter expert (SME) cognitive capability includes a data report dashboard module, and a rating module. The data report dashboard module includes an electronic hardware controller to generate an initial web analytics data report and to generate at least one inquiry associated with at least one abnormality included in the initial web analytics data report. The rating module detects at least one of a positive ranking and a negative ranking applied to a comment submitted by a user in reply to the at least one inquiry. The social networking-based web analytics data processing system further includes a subject matter expert (SME) identification module that identifies a SME based on at least one of social networking information, community expertise ranking and project stakeholder recognitions.

Abstract: The present disclosure relates to a system and method for identifying faults in a product or service. A processor receives a request comprising characterising data for identifying faults. The processor then selects multiple tester identifiers based on performance data associated with each of the multiple tester identifiers and based on the characterising data to generate a team record. After that, the processor generates a user interface associated with each of the multiple tester identifiers of the team record. The user interface comprises a user control element allowing a tester to provide a fault description. Through this user interface the processor receives multiple fault records that each comprises the fault description and are associated with one of the multiple tester identifiers of the team record. Finally, the processor stores each of the multiple fault records associated with the product or service and the associated tester identifier on a data store.

Abstract: An automated assessment process for rating, integrating, and reporting for assessment centers, based upon research is described, that takes the place of the traditional manual, clinical process, and corrects for potential human biases present using traditional assessment processes. The automated assessment process includes providing an assessment to a participant and receiving behavior ratings for one or more associated behaviors demonstrated by the participant during the assessment. The automated process also includes determining an initial competency rating based upon the behavior ratings. Each initial competency rating is combined with non-simulation assessment results and a final competency rating is determined for each competency being assessed. A report is then automatically generated that includes the final competency rating for each competency being assessed.

Abstract: Software techniques are described for making predictions and associated decisions regarding resource optimization for production efficiency, and scheduling associated actions accordingly. For example, with respect to a large workforce of employees eligible for available or potential training programs, techniques are described for making eligibility decisions regarding the training programs based at least in part on predicting whether and when an employee or subset of employees will depart a company, as well as on predicting a future business demand for the skills conferred by the training program(s). Similarly, with respect to machine resources, techniques are described for predicting whether and when a machine will malfunction, as well as for predicting a future demand for the functions provided by the new or upgraded machine functionality.

Abstract: Provided are methods and apparatus for matching postal addresses. In an example, provided is a method for comparing postal addresses. The method includes receiving a first postal address, standardizing the form of the first postal address, removing a component of the first postal address to create a canonical representation of the first postal address, and utilizing a signature-based algorithm to identify at least one stored signature which substantially matches the first postal address.

Abstract: A system and method for shipping an item is presented that reduces the number of steps involved in the physical process and protects shipper and recipient privacy. The shipper is not required to label a package with the shipper's name or address, the recipient's name or address, or proof of payment. Instead the shipper scans a barcode on the package that encodes a package identifier, and causes a recipient identifier and payment information to be associated with the package identifier in a database. The recipient then causes his or her address to be associated with the recipient identifier.