Abstract: Apparatuses, systems, methods, and computer program products are disclosed for machine learning results. An input module may receive user input identifying a value for a machine learning parameter. A display module may display one or more machine learning results for the identified machine learning parameter in response to the input module receiving the user input. An update module may dynamically update the displayed one or more machine learning results in response to the input module receiving additional user input identifying an additional value for the machine learning parameter. A pre-compute module may predetermine permutations of the machine learning results prior to the input module receiving the user input.

Abstract: Techniques for predicting a user response to content are described. According to various embodiments, a configuration file is accessed, where the configuration file includes a user-specification of raw data accessible via external data sources and raw data encoding rules. In some embodiments, the raw data includes raw member data associated with a particular member and raw content data associated with a particular content item. Thereafter, source modules encode the raw data from the external data sources into feature vectors, based on the raw data encoding rules. An assembler module assembles one or more of the feature vectors into an assembled feature vector, based on user-specified assembly rules included in the configuration file. A prediction module performs a prediction modeling process based on the assembled feature vector and a prediction model, to predict a likelihood of the particular member performing a particular user action on the particular content item.

Abstract: A system and method for artificial neural network processing includes, for example, modifying, by a computer processor, a value of a charge of a node of an artificial neural depending on a number of elapsed steps since a prior predefined significant event. A system and method includes, for example, providing by a processor a real-time representation of an artificial neural network and of graphical effects of a running of the neural network. A system and method includes, for example, automatically modifying the behavior of network nodes based on simultaneous occurrences of events.

Abstract: A method, an apparatus and an article of manufacture for determining a dropped pronoun from a source language. The method includes collecting parallel sentences from a source and a target language, creating at least one word alignment between the parallel sentences in the source and the target language, mapping at least one pronoun from the target language sentence onto the source language sentence, computing at least one feature from the mapping, wherein the at least one feature is extracted from both the source language and the at least one pronoun projected from the target language, and using the at least one feature to train a classifier to predict position and spelling of at least one pronoun in the target language when the at least one pronoun is dropped in the source language.

Abstract: Systems, methods, and computer-readable media for automating workflow access for a user are provided. A prior activity of a user at a first healthcare application session on a first user device may be determined. The prior activity may occur at a first location in a healthcare facility. Based on the prior activity of the user, as well as a role associated with the user and a second location of the user, a next activity of the user at a second healthcare application session may be predicted. The second healthcare application session may then be automatically launched.

Abstract: A system and method allowing machine analytics and multiple human analysts to work together in a collaborative fashion in the analysis of large amounts of data. The collaborative analysis promotes “sensemaking.” Sensemaking is the continued revising and expansion of a developing “story” so that it becomes more comprehensible. As the emerging story is refined, it should successfully incorporate more and more of the observed data and be more defensible with respect to contrary arguments.

Abstract: A weight management system can be implemented which assists a user in losing a target amount of weight before the conclusion of a weight loss program. Such a system can assign the user to a behavioral segment, and may further assign the user to an attitudinal segment as well. The weight management system can provide recommendations for the user's diet and exercise based on health information provided by the user and the segment or segments to which the user is assigned. These recommendations can be updated during the course of the weight loss program based on the user's continued progress or lack of the same.

Abstract: A computer-implemented method includes obtaining road sensor data reflecting speeds of traffic on road segments, transforming the road sensor data using vehicle probe data for the road segments reflecting vehicle speeds, and producing speed estimates for the road segments using the transformed road sensor data. The method can further include determining speeds for road segments between road sensors by smoothing data from sensors near the road segments.

Abstract: A computer-program causing a computing device to perform an association measurement between a target variable and each non-target variable of a data set; select non-target variables for inclusion in a visualization based on the degree of association; perform correspondence analysis between target values of the target variable and non-target values of each selected non-target variable; order target value markers within a target row based on the degrees of closeness; order non-target value markers within each non-target row based on the degrees of closeness; determine a width of each target value marker based on a frequency of occurrence of its target value in the data set; determine a width of each non-target value marker based on a frequency of occurrence of its non-target value in the data set; and cause generation of the visualization with connection markers emanating from the target value markers and extending among the non-target value markers.

Abstract: A computing device learns over time how to identify task reminders that are most likely to be helpful to a user in different contexts. The task reminders can remind the user of activities that the user needs to do. The computing device displays a graphical user interface (GUI) that contains the task reminders identified as being most likely to be helpful to the user in the user's current context. The computing device updates the task reminders in the GUI as the user's context changes. In this way, the computing device can present task reminders that are likely to be currently helpful to the user while suppressing task reminders that are less likely to be helpful to the user at the current time.

Abstract: Device, system, and method of detecting identity of a user based on motor-control loop model. A method includes: during a first session of a user who utilizes a pointing device for interacting with a computerized service, monitoring the pointing device dynamics and gestures of the user; based on the monitored dynamics and gestures, estimating parameters that characterize a sensorimotor control loop model of the user; storing in a database a record indicating that the user is associated with the parameters that characterize the sensorimotor control loop model of the user.

Abstract: Technologies are generally described for an invitation management scheme. In some examples, an application provider server may include an invitation request receiver unit configured to receive, from an account of a first user, a request to invite a second user to use an application; an interest determination unit configured to determine whether the second user is inclined to use the application based at least in part on behavior information regarding activity in an account of the second user that includes a number of invitations sent to the account of the second user that remain pending; a notification generation unit configured to generate an invitation to be sent to the account of the second user after the interest determination unit determines that the second user is inclined to use the application; and a notification transmitter unit configured to transmit the generated invitation to the account of the second user.

Abstract: A chronology-centric, defined-knowledge-domain information-handling methodology supported by a system featuring (a) a dynamic EDP data repository, (b) plural EDP case-entity chronologies stored in the repository in the forms of respective, internally time-stamped and chronologically-organized groups of EDPs that effectively define, case-entity-specific, respectively different stage-and-time EDP-condition identities of particular domain-associated subject matter, and (c) data-processing engine structure connected to the repository for recurrently and progressively interacting with the data repository in relation to at least one of constructing, re-constructing, accessing, and reporting the respective organizations, contents and significances of, selected case-entity chronologies, as well, if user requested at a particular point in time, as performing, and output reporting user-sought information associated with, relevant, selected, time-and-stage EDP-content registry alignments between different case-entity ch

Abstract: A constraint-based configurator receives a configuration property expressed as a numeric value. A calculation is performed using the numeric value and a constraint is evaluated based on the result of the calculation. An output is automatically displayed based on the evaluated constraint.

Abstract: A method for carrying out a learning function is described, which is used to provide at least one correction value to compensate for at least one nominal value deviation of at least one component of a motor vehicle. At least one characteristic is ascertained in the case of at least one defined operating state of the motor vehicle with the aid of the learning function and used to determine the at least one correction value. The method includes prompting a driver of the motor vehicle to operate the motor vehicle in the at least one defined operating state. A system for implementing a corresponding method is also described.

Abstract: An email activity pattern of a user is analyzed. A time probability for the user to act on an email sent to the user is determined based upon, at least in part, the email activity pattern of the user.

Abstract: The subject disclosure relates to automatically learning relationships among a plurality of manufacturing tool parameters as applied to arbitrary semiconductor manufacturing tools and a graphical user interface that is supported, at least in part, by an autonomous learning system. The graphical user interface can create one or more matrixes based on received data and can further generate additional matrices by transforming the one or more matrixes. A series of windows can be output, wherein the series of windows, provide performance analysis that comprises a matching between a focus chamber and a reference chamber. In an aspect, the focus chamber and the reference chamber can be different chambers. In another aspect, the focus chamber and the reference chamber can be the same chamber, which provides analysis of the deterioration in performance of the same chamber over time.

Abstract: An apparatus, system, and method are disclosed for defining normal usage of a computing system resource. A method for defining normal usage of a computing system resource includes receiving a repeating schedule that represents system usage of one or more computing resources and receiving one or more demand events that will affect the system usage of the one or more computer resources. The method also automatically creates a predictive temporal profile that represents the system usage of the one or more computer resources from information comprising the repeating schedule and the one or more demand events. The predictive temporal profile is displayed for the user to review.

Abstract: Systems and methods for detecting end of a transaction in a computing environment are provided. The method comprises determining a target area in a graphical user environment displayed on a display screen, wherein a change is expected to occur when end of a transaction is reached; masking the target area at least partially to remove content included in the target area that is present before or after the transaction was initiated; monitoring the target area for change in content; and detecting the end of the transaction when the content of the target area has changed.

Abstract: The invention concerns cyberpersonalities, including their and varied use in artificial reality. A cyberpersonality is comprised of a base personality (12). The base personality (12) is selected from a set of base personalities, each one representing the personality of a theoretical person. The cyberpersonality also includes a dynamic personality (14) that reflects the actual person (real or company) that the cyberpersonality is meant to represent and is able to learn. Information contained in the base (12) and dynamic (14) personality can be used to allow the person that the cyberpersonality mimics to interact in the artificial reality without direct control. The cybersonality can chat with third parties, including asking questions and answering questions, so as to learn more about each other. Other uses are related to searching, advertising and direct marketing.

Abstract: A method and system to evaluate data efficacy across an enterprise is disclosed. The method includes the step of indexing a set of data sources that include at least one of structured and unstructured data artifacts. The method further includes accessing the indexing on the one or more data sources with a computer. The method further includes the step of generating a plurality of analytics about the data sources based on the indexing, wherein the analytics include a plurality of: a document originality analytic, a corpus storage volume analytic, a data source ingest analytic, a document type analytic, and an analysis analytic. The method further includes displaying, on a display device, an interactive visualization of results based on the analytics, wherein the visualization comprises at least one of: a histogram, a graph, a timeline, a panel, a list, a chart, a popup, and a table.

Abstract: In one embodiment, a method includes receiving event information associated with an event listing, the event information being inputted by a user of an online event management system at a client device; transmitting the event information to the online event management system, the event listing being synchronously categorized with the sending of the event information; and receiving from the online event management system one or more categories associated with the event listing for display to the user at the client device, the categories being automatically determined based on categorization models of the online event management system in response to the transmitted event information.

Abstract: A method and system for processing incompatible NUI data in a meaningful and productive way. An NUI system capable of combining NUI events from multiple NUI devices and producing a standardized output is described. NUI adaptors covert low level input data into high-level NUI events. These events are stored in a repository. A behavioral analysis engine makes use of the stored NUI events and produces a combined output for users making use of behavioral pattern rules. The behavioral analysis engine also makes use of NUI events for training the system to create and utilize new pattern rules.

Abstract: A graphical programming interface for use in developing computer programs uses a structure of graphically displayed elements representing positions, arguments and linkages to enable the development of computational decision making programs. Linkages may implement simple functions including inverting the communicated values from the positions or arguments. Linkage function may be reflected in a graphical depiction of the linkage.

Abstract: A method of building classifiers for neurological assessment is described. The method comprises the steps of extracting quantitative features from a plurality of clinical features, and selecting a subset of features from the extracted pool of features to construct binary classifiers. A device for performing point-of-care neurological assessment using clinical features is also described.

Abstract: To administer computer network security, a computer system receives a bit string that encodes a natural-language request for adjusting a security policy of the network and parses the bit string to identify one or more objects and an action to be applied to the object(s). Preferably, the system displays a description of one of the objects and a menu of operations that are applicable to the object, receives a user selection of one of the options, and effects the selected operation. The scope of the invention also includes a non-transient computer-readable storage medium bearing code for implementing the method and a system for implementing the method.

Abstract: A method and system for inferring user attributes in a social networking system. The method includes maintaining a social graph comprising a plurality of nodes and a plurality of edges between the nodes. An unknown, incomplete, or inaccurate user attribute for a user is identified, and a plurality of probability lists are generated using a corresponding plurality of probability algorithms that utilize known user attributes and the social graph. The probability lists include a set of probability entries, each including a prediction we value for the unknown, incomplete, or inaccurate user attribute and a confidence score. Using the probability lists and a plurality of weights corresponding to the probability algorithms, an inferred user attribute value is generated and stored.

Abstract: System and method for automatically generate therapy plan parameters by use of an integrate model with extended applicable regions. The integrated model integrates multiple predictive models from which a suitable predictive model can be selected automatically to perform prediction for a new patient case. The integrated model may operate to evaluate prediction results generated by each predictive model and the associated prediction reliabilities and selectively output a satisfactory prediction. Alternatively, the integrated model may select a suitable predictive model by a decision hierarchy in which each level corresponds to divisions of a patient data feature set and divisions on a subordinate level are nested with divisions on a superordinate level.

Abstract: A system for creating and using a universal tag to gather consumer data from a website for the purposes of targeted advertising is provided. The universal tag system has two main subsystems. The first subsystem is a configuration system that is used to define the consumer data to be collected from the website and to define taxonomy and transformation rules to be applied to the collected consumer data. The second subsystem is a runtime system that runs a universal tag client-side script, which is triggered when a consumer lands on a webpage of the website, for collecting the defined consumer data. The runtime system then applies the transformation rules to the collected data and updates a user profile corresponding to the consumer with the transformed data. As well, the runtime system applies the taxonomy rules to the collected data and categorizes the consumer for the purposes of subsequent targeted advertising.

Abstract: A knowledge interface is provided that interacts with a user to identify a solution to a customer problem or issue with respect to a particular product or service. The knowledge interface includes data processing functionality configured to dynamically generate a number of components that are presented in at least one display window for display to the user. The components include first data identifying a set of predetermined symptoms linked to the problem or issue and related interface elements for classification of the set of predetermined symptoms, second data identifying a set of predetermined root causes linked to the set of predetermined symptoms and related interface elements for classification of the set of predetermined root causes, and third data identifying a set of solutions linked to the set of predetermined root causes. The third data identifies a best solution based upon the predetermined root causes and their associated class designations.

Abstract: Disclosed herein is system, method and architecture facilitating goal setting and achievement and providing positive social and economic motivators for goal achievement. Progress toward a goal is tracked and a determination may be made based the progress whether or not to initiate one or more actions to stimulate progress and/or increase the likelihood of success in achieving a goal and/or achieving a milestone in a path of progression toward the goal.

Abstract: Some embodiments of the invention provide a mobile device with a novel route prediction engine that (1) can formulate predictions about current or future destinations and/or routes to such destinations for the device's user, and (2) can relay information to the user about these predictions. In some embodiments, this engine includes a machine-learning engine that facilitates the formulation of predicted future destinations and/or future routes to destinations based on stored, user-specific data. The user-specific data is different in different embodiments. In some embodiments, the stored, user-specific data includes data about any combination of the following (1) previous destinations traveled to by the user, (2) previous routes taken by the user, (3) locations of calendared events in the user's calendar, (4) locations of events for which the user has electronic tickets, and (5) addresses parsed from recent e-mails and/or messages sent to the user.

Abstract: A mechanism for discerning user preferences for categories of provided content. A computer receives response data including a set of preference values that have been assigned to content items by content users. Output data is computed based on the response data using a latent factor model. The output data includes at least: an association matrix that defines K concepts associated with the content items, wherein K is smaller than the number of the content items, wherein, for each of the K concepts, the association matrix defines the concept by specifying strengths of association between the concept and the content items; and a concept-preference matrix including, for each content user and each of the K concepts, an extent to which the content user prefers the concept. The computer may display a visual representation of the association strengths in the association matrix and/or the extents in the concept-preference matrix.

Abstract: The subject disclosure is directed towards processing evidence, which may include high-dimensional streaming evidence, into a future belief state. The existing evidence is used to project a belief about a future state. The future belief state may be used to determine whether to wait for additional evidence, or to act now without waiting for additional evidence, e.g., based on a cost of the delay. For example, an autonomous assistant may decide based upon the belief whether to engage a person or not, or to wait for more information before the engagement decision is made.

Abstract: A computing system includes: a control unit configured to operate a knowledge discovery component to extract knowledge from data, operate a knowledge engineering component to perform a knowledge extension or a knowledge evolution on the data or the knowledge; and a user interface, coupled to the communication unit, configured to operate an interface component to interact with the knowledge discovery component and the knowledge engineering component.

Abstract: A learning health system and associated methods are provided. Biochemical assays are conducted at scheduled intervals on blood samples taken from an individual to provide, for each of a plurality of biochemical parameters, a time series of values representing the individual. Clinical parameters associated with the individual are extracted from a knowledge base. Genomic parameters are determined for the individual. An expected time series is calculated for each of a plural subset of the plurality of biochemical parameters from at least the clinical parameters and the genomic parameters. For each of the plural subset of biochemical parameters, the time series of values representing the individual is compared to the calculated expected time series to determine a likelihood of each of a plurality of conditions for the individual. The likelihood of at least one of the plurality of conditions is communicated to a user.

Abstract: A method of preparing a customized schedule of activities for a person afflicted with dementia, the method comprising (a) prompting a user with questions regarding the person's preferred activities, (b) compiling user responses regarding the person's preferred activities, (c) prompting a user with question concerning the person's ability to perform certain tasks, (d) compiling user responses regarding the person's abilities, (e) determining the person's stage of dementia based on the user responses regarding the person's abilities, and (f) based on the stage of dementia, generating a schedule of activities, the schedule of activities including essential activities and preferred activities, wherein time allocated between the essential and preferred activities in the schedule differs for different stages, and wherein the preferred activities depends at least in part on the responses received in step (b).

Abstract: Systems and methods for classifying electronic information or documents into a number of classes and subclasses are provided through an active learning algorithm. In certain embodiments, seed sets may be eliminated by merging relevance feedback and machine learning phases. In certain embodiments, the active learning algorithm forks a number of classification paths corresponding to predicted user coding decisions for a selected document. The active learning algorithm determines an order in which the documents of the collection may be processed and scored by the forked classification paths. Such document classification systems are easily scalable for large document collections, require less manpower and can be employed on a single computer, thus requiring fewer resources. Furthermore, the classification systems and methods described can be used for any pattern recognition or classification effort in a wide variety of fields.

Abstract: A method for providing a response to a statement of a user, the method includes: receiving user input that comprises a portion of a user statement; selecting, before receiving a whole user statement, an answerable statement response between an answerable statement, multiple answerable statements and a response to an answerable statement; wherein the selecting is responsive to user input and to structured representations of answerable statements answerable by an answering entity; and sending to the user information representative of response to the user statement.

Abstract: A system that helps users get unstuck determines an archetype to which the user's stuck moment belongs and then provides a diagnosis and one or more tools. Each archetype has a corresponding prescription, each prescription has a corresponding computer-implemented tool. The diagnosis for the person determines a prescription for that person, and the prescription for that person determines at least one computer-implemented tool for that person to deal with the stuck moment.

Abstract: A mobile terminal including a wireless communication unit configured to wirelessly communicate with at least one other terminal; a display unit configured to display screen information in a first region, and display an indicator area in a second region adjacent to the first region; and a controller configured to extract at least one keyword data included the displayed screen information, perform a search operation using the extracted keyword data, and display a result of the search operation in the second region.

Abstract: A method and a device for predicting a future occurrence of a transportation system incident are disclosed. The method includes receiving transportation incident data comprising information collected during and related to operation of at least one transportation vehicle, the information comprising at least a time stamp, constructing at least one count regression model based upon the transportation incident data, producing a results set based upon the at least one count regression model, predicting at least one future occurrence of an incident based upon the results set, and presenting the at least one predicted future occurrence. The device includes at least a processing device and computer readable medium containing a set of instructions configured to cause the device to perform the method.

Abstract: A method and system of determining a prioritized list of one or more users related to a given goal obtaining a set of places, determine one or more future places an expert associated with a given goal is predicted to visit to accomplish the given goal, obtain a history of one or more places users have visited, determine one or more historical places from the history of one or more places that match the future places, and identify one or more users associated with the determined one or more historical places.

Abstract: A multi-social network discovery system and method enables users to select multiple social networks comprising activity streams and to receive recommendations sourced from the selected multiple social networks. The multi-social network discovery system and method generates affinity values based on inferred affinity levels between topics, which may be associated with tags, and objects that are associated with the activity streams. The inferred affinity values may be derived from usage behaviors such as tagging and/or based on an automatic analysis of the content of the objects. The affinity values inform the selection of the objects to be recommended to a user, and the selection may be further informed by inferred affinity levels between the user and the topics. The recommendations may be tuned by the user through application of a recommendation tuning control.

Abstract: An optimality degree computation unit computes an optimality degree in the case where a first variable included in a variable set is a candidate for an addition variable, using an objective function. An addition threshold computation unit computes an addition threshold based on the computed optimality degree, the addition threshold being a threshold of the optimality degree and indicating a criterion for determining whether or not the first variable is to be set as the candidate for the addition variable. An objective function value computation unit computes an objective function value which is a difference between a value of the objective function computed using variables to be optimized and a value of the objective function computed using the variables to be optimized from which a second variable included in a nonzero variable set is excluded.

Abstract: A personal taste assessment and prediction system implements a method of predicting a person's preference for an item. The system may receive identifying information about an item of interest, and it may use the identifying information to access a database of characteristic values for various items and identify one or more characteristics of the item of interest. The system will access a user profile and process the retrieved characteristics with a user profile for a person to generate a predicted rating for the item of interest for the person.

Abstract: A system and method for data gathering system, comprising a data-aware knowledge base storing knowledge on relative costs of obtaining various data items; and a data retrieval decision-making processor operative, when an individual data element is sought to be retrieved, to determine whether or not to retrieve the data element by comparing at least one parameter representing need for the data element, also termed herein a utility value, with at least one parameter, retrieved from the data-aware knowledge base, which represents relative cost of obtaining the data element.

Abstract: Computer implemented techniques for classifying mental states of individuals are described. The techniques determine sets of words that are associated with multiple groups having different mental status, and a classification model is used to classify one group against another group. Furthermore, by determining points of intersection of words between a first group and second group, words that are statistically predictive terms and that are unique to each group, to provide further predictive features for differentiating the multiple cohorts.

Abstract: A computer-based sleep improvement system applying system intelligence to up-to-date user-reported data and/or recorded sleep data from a connected tracking device for assisting a user in the proactive improvement of sleep and treatment of insomnia includes a central server maintaining a library of information related to treatment of insomnia. The central server includes a video database of session video material, an audio database of session material, a case file database of information regarding the user and sleep habits of the user, and a plurality of tools assisting the user in treating insomnia. The system includes a session coordinator creating sessions of customized presentations for the user based upon the library of information and a user interface linked to the central server.

Abstract: Systems and methods for culture mapping and intelligence include software tools to collect, analyze, and categorize data based on behavior archetypes to produce information visualizations from the data. In one embodiment, a user query relative to a topic of interest may include a word, a combination of words, or a set of words for a particular field, such as a byline or hashtag of an online or networked community. One or more data sources, which may include social media and other websites are selected by the user or the system and a list of accounts ordered by one or more selected criteria, such as frequency of occurrence of the query words, for example, is produced. One or more weighting factors may then be associated with each account. A matrix is generated with accounts positioned to illustrate the account relative to behavior attributes along selected continuums.