Abstract: Techniques for identification of a trigger-type leader in a social network are described. According to various embodiments, a specific content item posted by a particular actor of a plurality of actors and interactions by other actors of the plurality of actors with the specific content item are identified. A leadership score associated with the particular actor is then calculated, the leadership score indicating a propensity of the particular actor to stimulate discussion among actors of the online social network service. The particular actor is then classified as an information trigger among the plurality of actors of the online social network service, based on the calculated leadership score.

Abstract: Methods, apparatuses and systems directed to pattern identification and pattern recognition. In some particular implementations, the invention provides a flexible pattern recognition platform including pattern recognition engines that can be dynamically adjusted to implement specific pattern recognition configurations for individual pattern recognition applications. In some implementations, the present invention also provides for a partition configuration where knowledge elements can be grouped and pattern recognition operations can be individually configured and arranged to allow for multi-level pattern recognition schemes.

Abstract: A method for the management of artifacts in knowledge ecosystems is disclosed. The management of artifacts may be performed through the interaction of project participants with a computing device which may display a project repository interface of a software module within a knowledge ecosystem. The method may include the process to retrieve an artifact from a knowledge base to store in the project repository, and the process to store a new artifact in the knowledge base. Moreover, the method may include a process for associating a retention policy, a quality rank and suitable categories and tags to each artifact stored in the knowledge base, which may facilitate the selection of a suitable artifact according to the project requirements. As a result, the method for the management of artifacts may allow leveraging human expertise, saving human efforts, improving decision-making and fostering innovation.

Abstract: An apparatus for determining a user's mental state in a terminal is provided. The apparatus includes a data collector configured to collect sensor data; a data processor configured to extract feature data from the sensor data; and a mental state determiner configured to provide the feature data to an inference model to determine the user's mental state.

Abstract: This disclosure relates to a system and method for determining responsiveness of a driver of a vehicle to feedback regarding driving behaviors. The system may include a sensor configured to generate output signals conveying first driving behavior information, which may characterize operation of the vehicle by the driver. The system may include one or more processors configured to obtain the first driving behavior information. The one or more processors may effectuate provision of feedback defined by feedback information based on the first driving behavior. The sensor may be configured to output signals conveying second driving behavior information, which may characterize operation of the vehicle by the driver during and/or subsequent to the provision of the feedback. The one or more processors may be configured to obtain the second driving behavior information and assess responsiveness of the driver to the feedback based on the second driving behavior information.

Abstract: In an embodiment of the present disclosure, a method for modeling prediction of inhalable particles concentration is disclosed. In the method, at least one dispersal event is identified, and at least one accumulation event is identified based on the identified at least one dispersal event. Then a dispersal prediction model is generated based on the identified at least one dispersal event. Then at least one accumulation level of inhalable particles concentration is obtained for the at least one accumulation event. A change prediction model for the accumulation level is generated. Then a plurality of accumulation prediction models is generated.

Abstract: In one embodiment, a method includes training a deep neural network using a first set of network characteristics corresponding to a first time and a second set of network characteristics corresponding to a second time, generating, using the deep neural network, a predictive set of network characteristics corresponding to a future time, and assigning a task of a distributed application to a processing unit based on the predictive set of network characteristics.

Abstract: Embodiments of the invention provide a system for scaling multi-core neurosynaptic networks. The system comprises multiple network circuits. Each network circuit comprises a plurality of neurosynaptic core circuits. Each core circuit comprises multiple electronic neurons interconnected with multiple electronic axons via a plurality of electronic synapse devices. An interconnect fabric couples the network circuits. Each network circuit has at least one network interface. Each network interface for each network circuit enables data exchange between the network circuit and another network circuit by tagging each data packet from the network circuit with corresponding routing information.

Abstract: A method of training an artificial neural network The artificial neural network comprising a plurality of connections connecting nodes arranged in at least an initial and a subsequent layer. The method comprises receiving a training example, the training example having input values, a target, and an associated training salience value indicating an importance of the input values to determining the target. The method further comprises determining salience values for nodes of the initial layer from the training salience value; determining an activation value for at least one node of the subsequent layer by propagating the input values using a subset of the connections selected based on the determined salience values for the nodes of the initial layer; and training the artificial neural network using the activation value, the trained artificial neural network configured to determine a relationship between the input data values and the target.

Abstract: A rating prediction engine builds and applies models to predict ratings based on an analysis of textual reviews and comments. The engine can build multiple models simultaneously through distributed parallel model building that employs deep convolutional neural networks (CNNs). The engine can also incorporate user moment feature data, including user status and context information, to provide better performance and more accurate predictions. The engine can also employ heuristic unsupervised pre-training and/or adaptive over-fitting reduction for model building. In some instances, the techniques described herein can be used in a service to predict personalized ratings for reviews or other published items, in instances where the original author of the item did not include a rating and/or in instances where the publication channel does not provide a mechanism to enter ratings.

Abstract: System and method for conversion of virtual machine files without requiring copying of the virtual machine payload (data) from one location to another location. By eliminating this step, applicant's invention significantly enhances the efficiency of the conversion process. In one embodiment, a file system or storage system provides indirections to locations of data elements stored on a persistent storage media. A source virtual machine file includes hypervisor metadata (HM) data elements in one hypervisor file format, and virtual machine payload (VMP) data elements.

Abstract: A machine learning system for evaluating at least one characteristic of a heart valve, an inflow tract, an outflow tract or a combination thereof may include a training mode and a production mode. The training mode may be configured to train a computer and construct a transformation function to predict an unknown anatomical characteristic and/or an unknown physiological characteristic of a heart valve, inflow tract and/or outflow tract, using a known anatomical characteristic and/or a known physiological characteristic the heart valve, inflow tract and/or outflow tract. The production mode may be configured to use the transformation function to predict the unknown anatomical characteristic and/or the unknown physiological characteristic of the heart valve, inflow tract and/or outflow tract, based on the known anatomical characteristic and/or the known physiological characteristic of the heart valve, inflow tract and/or outflow tract.

Abstract: A method and apparatus used for general purpose problem solving using entanglement properties of holography. Intelligent point-based entities having spatial and other electromagnetic properties called DROPLETS [Data-Representative-Object-Particle(s)-Liking-EnTanglement] are generated as avatars, or delegate objects, connected to concrete or abstract data sources representing a situation, event or other problem. Each DROPLET's properties are controlled by changes in the input sources, feedback, changes in itself, and/or changes of other DROPLETS. Coherent rays are introduced and interact with said DROPLETS, generating an INTELLIGENCE WAVEFRONT. Interference patterns are recorded and converted to binary machine codes used as instruction keys to store and lock human readable and/or machine readable content components into a plurality of associative memories. Said content includes waveforms, harmonics, codes, data, and other holograms.

Abstract: Embodiments of the present invention provide a method for feature extraction using multiple neurosynaptic core circuits including one or more input core circuits for receiving input and one or more output core circuits for generating output. The method comprises receiving a set of input data via the input core circuits, and extracting a first set of features from the input data using the input core circuits. Each feature of the first set of features is based on a subset of the input data. The method further comprises reordering the first set of features using the input core circuits, and generating a second set of features by combining the reordered first set of features using the output core circuits. The second set of features comprises a set of features with reduced correlation. Each feature of the second set of features is based on the entirety of said set of input data.

Abstract: Presenting ancestral origin information, comprising: receiving a request to display ancestry data of an individual; obtaining ancestry composition information of the individual, the ancestry composition information including information pertaining to a proportion of the individual's genotype data that is deemed to correspond to a specific ancestry; and presenting the ancestry composition information to be displayed.

Abstract: A clothing search system provides a clothing search to users using a component-based image search. Retailer catalogs are analyzed to determine clothing components within clothing images. Features associated with the components are determined. When a user requests a clothing search, the clothing search system selects clothing based on the components and features requested by the user. The user may also provide an image to the clothing search system. The clothing search system determines components and features of the image and identifies clothing with matching components.

Abstract: A system and methodology which can effectively provide decision makers with a better means of making decisions in a way that greatly improves the availability, reliability, and relevance of the information which they provide and use to make decisions. The system and methodology facilitates maximizing mutual utility in the context of a mutual decision between multiple users and groups of users identified generally as Parties and Counterparties and performs user specified actions based on meeting mutual threshold parameters. The system provides significant technical advantages over the prior art in that it uses helps Parties and Counterparties identify optimal arrangements and configurations with less errors, fewer computational cycles, less storage medium, and a smaller amount of time than would be possible using prior art systems.

Abstract: Methods and systems for analysis and/or classification of electronic message information so as to capture and identify salient objects exchanged during electronic message passing in order to impute certain information about the object, groups of objects, the message, groups of messages, the parties, communities involved in the message exchange or combinations, thereof.

Abstract: The various implementations described herein include systems and methods for determining that media items are currently being presented. In one aspect, a method performed at a client device includes: (1) identifying a media item potentially being presented on an output device coupled to the client device; (2) calculating a level of confidence that the identified media item is currently being presented to the user; (3) subsequent to the calculating, determining that at least one predetermined event associated with user interaction with the media item has occurred; and (4) based on the at least one predetermined event, increasing or decreasing the level of confidence that the identified media item is currently being presented to the user.

Abstract: Provided is an information processing apparatus, including a calculation section which calculates a proficiency level of a user for operations performed by the user for achieving a prescribed objective based on history information related to the operations and attribute information related to physical features of the user, and a generation section which generates advice for achieving the objective based on the proficiency level calculated by the calculation section.