Abstract: An apparatus and a method for determining careless driving are provided and determine more reliable careless driving by generating normal driving patterns using driving performance data for a reference time at the beginning of driving. In addition, careless driving patterns greater than a predetermined number are detected using the normal driving pattern and a boundary between the normal driving and the careless driving is determined using a supervised learning method. The careless driving of the driver is then determined based on the determined boundary.

Abstract: An NFA (Non-deterministic Finite Automaton) circuit includes a hardware byte characterizer, a first matching circuit (performs a TCAM match function), a second matching circuit (performs a wide match function), a multiplexer that outputs a selected output from either the first or second matching circuits, and a storage device. N data values stored in first storage locations of the storage device are supplied to the first matching circuit as an N-bit mask value and are simultaneously supplied to the second matching circuit as N bits of an N+O-bit mask value. O data values stored in second storage locations of the storage device are supplied to the first matching circuit as the O-bit match value and are simultaneously supplied to the second matching circuit as O bits of the N+O-bit mask value. P data values stored in third storage locations are supplied onto the select inputs of the multiplexer.

Abstract: Methods and system for providing information selected from a large set of digital content to a user. Techniques include receiving user context information associated with the user and identifying or generating a first concept in a semantic network, the first concept representing at least a portion of the user context information. The method further comprises obtaining at least one concept, including a second concept, semantically relevant to the first concept at least in part, by synthesizing the second concept based on the first concept and at least one other concept in the semantic network; and providing information to the user, wherein the information is selected by using the first concept and the at least one obtained concept semantically relevant to the first concept, wherein the first concept in a semantic network is represented by a data structure storing any data associated with a node in the semantic network.

Abstract: Systems and methods for generating and using measurable indexes for providing a total wellness assessment of an individual are provided. A method includes computing an overall health score corresponding to the individual based on a plurality of weighting factors, the weighting factors based at least on health conditions associated with the individual. The method also includes determining a set of recommended changes for the individual based on the overall health score and generating an episodic plan for the individual, the episodic plan comprising a series of episodes for the individual that when completed will result in the individual having implemented the set of recommended changes. The method further includes generating a series of prompts for the individual, the series of prompts selected to guide the individual through the episodic plan.

Abstract: Systems and methods for the annotation of source data using confidence labels in accordance embodiments of the invention are disclosed. In one embodiment of the invention, a method for determining confidence labels for crowdsourced annotations includes obtaining a set of source data, obtaining a set of training data representative of the set of source data, determining the ground truth for each piece of training data, obtaining a set of training data annotations including a confidence label, measuring annotator accuracy data for at least one piece of training data, and automatically generating a set of confidence labels for the set of unlabeled data based on the measured annotator accuracy data and the set of annotator labels used.

Abstract: The present invention relates to a data-processing device, characterized in that it includes, in combination: a memory (10) which is organized into two spaces, one containing attributes describing the stored data, and the other containing connectivity links among the stored data, and which is organized according to one or more dimensions respectively associated with attributes and divided into one or more hierarchized segments, the data being informed by creating, deleting, or modifying attribute values characterizing said segments; a means (11) for integrating one or more incoming information streams, which analyzes said streams in order to determine the data constituting same and to structure said data and the attributes thereof according to the organization of said memory (10); an inference engine (14) implementing, in parallel or in series, inference rules (141) grouped together in libraries (15), said rules (141) being programmed to regenerate a sequence including at least one segment of the memory, by c

Abstract: A system, method and computer program product for facilitating collaborative decision making may be provided. The system receives data representing individual postings of users associated with a deliberation to make a decision. The system further receives ratings associated with the individual postings in order to make the decision. The system represents the received data in a hierarchical data structure. The system aggregates, through the hierarchical data structure, the ratings associated with the individual postings to obtain strength values. The system facilitates the making of the decision based on the aggregated strength values.

Abstract: A method for detecting an abnormal transition pattern from a transition pattern includes: first extracting an episode pattern with an appearance frequency greater than or equal to a first frequency from an episode pattern represented with a description form so as to include a first transition pattern and a second transition pattern differing in an order of a part of items from the first transition pattern to have a complementary relation thereto; second extracting a third transition pattern with an appearance frequency greater than or equal to a second frequency from the transition pattern; and specifying a transition pattern other than the third transition pattern from transition patterns included in the extracted episode pattern, and determining an abnormal transition pattern based on the transition pattern specified in the specifying when the third transition pattern includes a fourth transition pattern corresponding to the extracted episode pattern in the first extracting.

Abstract: A computer system iteratively executes a decision tree-based prediction model using a set of input variables. The iterations create corresponding rankings of the input variables. The computer system generates overall variables contribution data using the rankings of the input variables and identifies key input variables based on the overall variables contribution data.

Abstract: A method and system for analysis of data, including creating a first node, determining a first hyper-cube for the first node, determining whether a sample resides within the first hyper-cube. If the sample does not reside within the first hyper-cube, the method includes determining whether the sample resides within a first hyper-sphere, wherein the first hyper-sphere has a radius equal to a diagonal of the first hyper-cube.

Abstract: A computerized method for detecting a change point in a data stream by testing whether two sets of samples from the data stream were derived from the same distribution, wherein the test uses the unique convergence properties of the two sample tests to probabilistically find the point which maximizes their value, said point closely approximating the change point.

Abstract: A media control system enables a device-agnostic and source-agnostic entertainment experience through use of an internet-enabled user device. The user device includes a client application for navigating through media or entertainment content, controlling media devices according to a type of media content selected by the user, and sharing media experiences via social networks. The user device includes smartphones, tablet computers, and other internet-enabled processor-based devices. The media control system leverages the internet access of the user device to enable search and discovery of all available media content. A recommendation engine coupled to the client application learns media preferences from user behavior, generates from numerous disparate media sources recommended media choices corresponding to the media preferences, and presents the recommended media choices on the user device.

Abstract: A method of emulating the human brain with its thought and rationalization processes is presented here, as well as a method of storing human-like thought. The invention provides for inclusion of psychological profiles, experience and societal position in an electronic emulation of the human brain. This permits a realistic human-like response by that emulation to the people and the interactive environment around it.

Abstract: A method for classifying unclassified vehicle tracks using real-time sensor data comprises acquiring a computer database of vehicle track characteristics data for known vehicle tracks; defining vehicle track signatures based on the vehicle track characteristics data; and generating a graph based on the vehicle track signatures, the graph having state nodes representative of distinguishing vehicle track characteristics defined in the vehicle track signatures and links between the state nodes representative of relationships between distinguishing vehicle track characteristics defined in the vehicle track signatures, said graph also having reporting nodes for classifying unknown vehicle tracks when sufficient distinguishing vehicle track characteristics have been observed. The method also comprises processing with the graph, using a processor, real-time sensor data corresponding to a first unclassified vehicle track until the first unclassified vehicle track is classified.

Abstract: A predictive model forecasts a medical resource need by making use of empirical Bayes estimation methods to determine a Dynamic Bayes Network (DBN) model. Exemplary resource needs that may be forecast include nurses, ventilators, hospital rooms, etc. The DBN model is estimated from retrieved data that is related to the resource to be forecast. The DBN model is simplified and a predictive model is generated based on the simplified model. The predictive model runs to forecast the predicted need for the resource. Embodiments are directed toward a predictive model development system that instructs an operator as to the structure of the data so that a model may be tailored based on the understanding of the operator. Embodiments are directed toward a model running system that indexes available models and also employs powerful statistical analysis techniques on behalf of a user to generate a predictive model with little or no user involvement in low-level modeling details.

Abstract: Multiple classifiers can be applied independently to evaluate images or video. Where there are heavily imbalanced class distributions, a local expert forest model for meta-level score fusion for event detection can be used. Performance variations of classifiers in different regions of a score space can be adapted. Multiple pairs of experts based on different partitions, or “trees,” can form a “forest,” balancing local adaptivity and over-fitting. Among ensemble learning methods, stacking with a meta-level classifier can be used to fuse an output of multiple base-level classifiers to generate a final score. A knowledge-transfer framework can reutilize the base-training data for learning the meta-level classifier. By recycling the knowledge obtained during a base-classifier-training stage, efficient use can be made of all available information, such as can be used to achieve better fusion and better overall performance.

Abstract: A Stateful Reference Monitor can be loaded into an existing commercial operating system, and then can regulate access to many different types of resources. The reference monitor maintains an updateable storage area whose contents can be used to affect access decisions, and access decisions can be based on arbitrary properties of the request.

Abstract: A combined computer/human approach is used to detect actionable insights in large data sets. Automated computer analysis used to identify patterns (e.g., possibly meaningful patterns or subsets within the data). These are presented to humans for feedback, where the humans may have little to no training in the statistical methods used to detect actionable insights. Feedback from the humans is used to improve the pattern detection and facilitate the detection of actionable insights.

Abstract: A method for analyzing adverse effects resulting from the use of a substance of interest, including identifying a substance of interest; selecting from multiple profiles related to the safety of the substance of interest, using at least one filter; at least one data mining engine; and an output device for displaying the analytic results from the data mining engine. The data mining engine is selected from (1) a proportional analysis engine; (2) a comparator, and (3) a correlator; whereby a user can receive analytic results from the selector, the proportional analysis engine, the comparator, and the correlator.

Abstract: Disclosed are methods of constructing systems for predicting a subject's medical outcome. Also disclosed are methods and systems for predicting a subject's medical outcome. The disclosed methods and systems can include identifying a group of subjects with the same medical condition and classifying this group of subjects into one or more subgroups. The subgroups are classified based on similarity of medical outcome, using classification and regression trees (CART) to generate a classification tree based on the presence of identifying genetic characteristics. Each node in the classification tree describes the presence of a specific genetic marker and each branch in the classification tree describes a genetic profile that predicts a subject's medical outcome.