Abstract: A plurality of potential fault scenarios are accessed, wherein a given potential fault scenario of the plurality of potential fault scenarios has at least one corresponding root cause, and a representation of the given potential fault scenario comprises a don't care value. An actual fault scenario from telemetry received from a monitored system is generated. The actual fault scenario is matched against the plurality of potential fault scenarios. One or more matched causes are output as one or more probable root cause failures of the monitored system.

Abstract: Methods, apparatus, and processor-readable storage media for automatically identifying and correcting erroneous process actions using artificial intelligence techniques are provided herein. An example computer-implemented method includes discovering, during execution of a given process, one or more process action variants by processing data related to the given process using at least a first set of artificial intelligence techniques; categorizing at least a portion of the discovered process action variants into one or more groups based at least in part on historical process-related data and at least one density-based clustering algorithm; determining at least one resolution action in response to at least a portion of the one or more discovered process action variants by processing data pertaining to the one or more groups using at least a second set of artificial intelligence techniques; and performing the at least one determined resolution action.

Abstract: Methods and Systems implement patient management. In some cases, a patient management system 200 may include one or more respiratory pressure therapy devices to deliver respiratory pressure therapy to patients, and generate therapy data relating to a therapy session for a patient. The patient management system may include a data server communicating with the therapy device(s). The data server may compute, from therapy data, therapy summary data for the session, the summary data may include one or more statistics summarising therapy data. The patient management system may include a therapy management server communicating with the data server. The therapy management server may apply one or more rules to the summary data, update or generate one or more workflow groups of patients, each workflow group corresponding to a rule, depending on results of the respective rule applications; and/or serve a graphical layout representing one or more workflow groups.

Abstract: According to some embodiments, systems and methods are provided to develop or provide common sense auto-generated explanations (CAGE) for the reasoning used by an artificial intelligence, neural network, or deep learning model to make a prediction. In some embodiments, the systems and methods use supervised fine-tuning on a language model (LM) to generate such explanations. These explanations may then be used for downstream classification.

Abstract: A method for rendering context based information on a user interface includes receiving a user request to extract the context based information from a database. The database includes a plurality of documents and the request includes at least one search criteria required to determine a context of the user request. The method includes generating a list of documents corresponding to the context of the user request and rendering on a viewing portion of the user interface the list of documents corresponding to the context of the user request.

Abstract: In an approach for JAVA Virtual Machine (JVM) heap memory tuning, one or more computer processors obtain a feature vector of an application running on the JVM. The one or more computer processors input the feature vector to a predictive model trained with historical application data collected in one or more production environments. The one or more computer processors receive an output of the predictive model based on the feature vector with at least one memory tuning recommendation for the JVM. The one or more computer processors tune the memory of the JVM based on the at least one memory tuning recommendation.

Abstract: Some aspects provide: analyzing data exchange database records of a first entity; determining a sector with which the first entity is associated by at least one of the analyzing and first entity input identifying the sector; analyzing data exchange database records of second entity(ies) different from the first entity, to determine sector associated second entity(ies) data exchanges; analyzing the sector associated second entity(ies) data exchange records to determine data baseline(s); analyzing the first entity data exchange records to determine first entity data baseline(s), at least one of which corresponding in type to a respective one of the data baseline(s); comparing one of the data baseline(s) to a corresponding one of the first entity data baseline(s); identifying the relevant information based on the comparing; and notifying, via a communication module of the computing device, over a network, an electronic device associated with the first entity of the relevant information.

Abstract: Disclosed is a method for publishing a post. The method includes: in response to receiving a first publish request from a first terminal, first determining, based on location information of the first terminal, whether the first terminal is positioned in a delimited area; and publishing, based on a topic, a post carried in the first publish request only when the first terminal is positioned in the delimited area. Apparatuses for publishing posts and storage mediums are also provided.

Abstract: Systems, devices, and methods for carrying out communications on a drilling rig are presented. A drilling collaboration platform may be used to schedule tasks on the drilling rig and communicate with third parties. The drilling collaboration platform may be configured to generate vendor lists, send notifications and alerts to third parties, generate forms required for completing tasks, and gather data from the drilling rig.

Abstract: In one aspect, there is provided a method comprising: receiving consumption data comprising readings from one or more utility meters associated with a property comprising one or more devices, the one or more devices comprising one or more devices of interest; determining, in the received consumption data, one or more positive consumption variations indicative of switching on of one or more of the devices and/or one or more negative consumption variations indicative of switching off of one or more of the devices; identifying one or more events associated with the one or more devices, based on the determined variations, by matching one or more positive variations with one or more negative variations; grouping the identified one or more events into one or more blocks, each block corresponding to an occurrence of usage of a device of the property; classifying the one or more blocks into one or more predetermined clusters, the one or more predetermined clusters comprising a respective predetermined cluster associa

Abstract: Systems and methods are provided for efficiently performing processing intensive operations, such as those involving large volumes of data, that enable accelerated processing time of these operations. In at least one embodiment, a system includes a graphics processor unit (GPU) including a memory and a plurality of cores. The plurality of cores perform a plurality of data analytics operations on a respectively allocated portion of a dataset, each of the plurality of cores using only the memory to store data input for each of the plurality of data analytics operations performed by the plurality of cores. The data storage for the plurality of data analytics operations performed by the plurality of cores is also provided solely by the memory.

Abstract: The disclosure relates to a method, network node and service instance, the method being executed by a service provider, for optimizing resource allocation according to the needs of at least one client and according to an SLA between the client and the service provider. The method comprises obtaining a statistical behavior of a workload forecast function associated with a service of the client, obtaining a forecast value for a future workload from the workload forecast function associated with the service of the client, obtaining at least one service-level objective associated with the SLA between the client and the service provider, obtaining a modified forecast value based on the forecast value, the statistical behavior of the workload forecast function and service-level objective associated with the SLA, and adjusting resources allocated to the service based on the modified forecast thereby optimizing resource allocation for the at least one client.

Abstract: An analytic application may automatically determine a root cause of an issue with a wireless carrier network and generate a solution for the root cause. Initially, a data management platform may receive performance data regarding user device and network components of a wireless carrier network from multiple data sources. Subsequently, the analytic application may receive an indication of an issue affecting one or more user devices that are using the wireless carrier network. The analytic application may analyze the performance data using a trained machine learning model to determine a root cause for the issue affecting the one or more user devices. The trained machine learning model may employ multiple types of machine learning algorithms to analyze the performance data. The analytic application may provide the root cause or the solution that resolves the root cause for presentation.

Abstract: Methods and systems for performing root cause analysis for information technology incident management using cognitive computing are disclosed. A method includes: generating, by a computing device, a cache including a plurality of links between causes and solutions; obtaining, by the computing device, information about a current incident; generating, by the computing device, search keys from the information about the current incident using natural language processing; searching, by the computing device, the cache using the search keys; iteratively generating, by the computing device, new search keys using results from a previous search and searching the cache using the new search keys; and displaying, by the computing device, solutions based on results from the searching and the iteratively generating and searching.

Abstract: Provided are architectures, system, methods, and computer program products that provide a user with the ability to define an association of data and/or information from known reference sets perceived by the user as relevant to a subject matter domain, thereby imparting and formalizing some of the user's knowledge about the domain. An associative relevancy knowledge profiler may also allow a user to create a profile by modifying or restricting the known reference sets and windowing the results from the association as a user might refine any other analysis algorithms. An associative relevancy knowledge profiler may also be used to define a user profile used by the user and others. A user profile may be usable in various manners depending upon, for example, rights management permissions and restrictions for a user.

Abstract: A skip behavior analyzer is part of a media delivery system that allows for unbiased A/B testing of a plurality of versions of a song. The media delivery system stores a plurality of versions of a song and randomly selects, for each requesting device, a version of the song to associate with that device. Each time the device requests the song, thereafter, the media delivery system will provide the same version of the song for consistency. The media delivery system then gathers song play and skip information, calculates the differences in distribution of the skip behavior, and provides the skip information to allow a music composer to better determine which version of a song is more popular and why that is so.

Abstract: A distributed software application and communications terminal are provided which allows for increased situational awareness, and faster, more informed decision making for both floor and non-floor exchange derivatives traders. The present invention gives traders an enhanced situational awareness by using dial displays and calibration capabilities. The method has several closely interrelated modes and embodiments tailored to allow traders to maintain instant-glance situational awareness of a market, or of several markets. The present invention presents an alert for a trade, or for targeting yields, via a plethora of modes and specially juxtaposed graphical layouts. Calibration and recalibration capabilities are provided to enhance real-time analysis for traders.

Abstract: Aspects of the present disclosure relate to task template generation and social task discovery. In examples, a task template catalog comprises task templates, which may be automatically generated and/or user-submitted, among other examples. Task templates can be reviewed, shared, and curated within the task template catalog. A user may browse the task catalog or search the task catalog for task templates. Once the user selects a task template, a task is generated based on the task template and added to the user's task list. In some examples, aspects of a task template may be customized. For example, a task may comprise parametric or conditional subtasks, thereby enabling a user to further tailor the task template to his or her needs. Thus, the task catalog provides a starting point from which the user can author a task in a task management application.

Abstract: One embodiment provides a method, including: receiving, in an environment for developing a conversational tutor, domain content corresponding to a domain of the conversational tutor, wherein the conversational tutor comprises a conversational agent designed to assist students in learning a domain; receiving, at the environment, tutoring content developed by a user, wherein the tutoring content comprises a tutoring script comprising questions to be presented to the student during a tutoring session with the conversational tutor to assist the student in learning the domain; evaluating, within the environment, the tutoring content against the domain content, wherein the evaluating comprises (i) identifying missing tutoring content, (ii) identifying the difficulty of the tutoring content, and (iii) identifying question dependencies; and providing, at the environment, at least one recommendation, identified from results of the evaluation, for adjusting the tutoring content.

Abstract: A method and system for identifying workplace risk factors is provided. The method includes monitoring via execution of multiple geographically distributed sensor devices, workplace injury based events associated with individuals at a multisite distributed workplace environment. Current injury data describing the workplace injury based events is stored and predicted future workplace injury based events associated with future workplace injury based events with respect to a predicted plurality of individuals at the multisite distributed workplace environment are determined. Injury risk mitigating actions associated with prevention of said predicted future workplace injury based events are generated and an associated cost optimized reduction plan for prioritized implementation of the injury risk mitigating actions is generated.

Abstract: A system to manage power consumption from a grid includes a building switchgear; an independent system organization (ISO) meter coupled to the building switchgear, the ISO meter including a telemetry unit to communicate with an ISO; and an energy storage system (ESS) coupled to the building switchgear, wherein the ESS selectively provides power in response to a customer power demand to prevent a customer grid power consumption from spiking and peaking at grid imbalance highest cost on peak times.

Abstract: Methods and apparatus related to ranking modifications of a previous query. For example, modifications of a previous query may be generated based on a current query issued subsequent to the previous query by substituting one or more n-grams of the previous query with one or more n-grams of the current query. One or more measures of each of the modifications may be identified and, based on such measures, a ranking of each of the modifications may be determined. One of the modifications may be selected as a submission query based on the rankings of the modifications. The submission query may be selected for submission in lieu of, or in addition to, the current query.

Abstract: An arrival/departure management device performs near-field communication with a wireless communication terminal and identifies a user of the wireless communication terminal, registers a time of arrival or departure for the user of the wireless communication terminal that was identified, and sends or receives information corresponding to the identified user on the basis of the registered content.

Abstract: An apparatus and method are provided for a managed knowledge network platform (KNP). Model dissimilarity values for model pairs are obtained, each model pair including a first model of a plurality of models in a KNP and a different model in the plurality of models. Path lengths between a first model node of a plurality of model nodes in the KNP and each one of other model nodes are computed, where the first model node represents the first model and the first model node is connected to a first user node of a plurality of user nodes representing users of the KNP. At least one of the different models is selected based on the model dissimilarity values and the path lengths. A recommendation that includes the at least one model is generated for a first user represented by the first user node.

Abstract: Systems and methods for using autoencoders for training natural language classifiers. An example method comprises: producing, by a computer system, a plurality of feature vectors, wherein each feature vector represents a natural language text of a text corpus, wherein the text corpus comprises a first plurality of annotated natural language texts and a second plurality of un-annotated natural language texts; training, using the plurality of feature vectors, an autoencoder represented by an artificial neural network; producing, by the autoencoder, an output of the hidden layer, by processing a training data set comprising the first plurality of annotated natural language texts; and training, using the training data set, a text classifier that accepts an input vector comprising the output of the hidden layer and yields a degree of association, with a certain text category, of a natural language text utilized to produce the output of the hidden layer.

Abstract: Technologies for managing telemetry and sensor data on an edge networking platform are disclosed. According to one embodiment disclosed herein, a device monitors telemetry data associated with multiple services provided in the edge networking platform. The device identifies, for each of the services and as a function of the associated telemetry data, one or more service telemetry patterns. The device generates a profile including the identified service telemetry patterns.

Abstract: A method for generating stylistic feature prescriptions to align a body of text with one or more target goals includes receiving, at a stylistic feature model, a body of text, where the body of text is selected by a user via a graphical user interface (GUI). The stylistic feature model identifies stylistic features from the body of text and populates a stylistic feature vector with the stylistic features. A trained de-confounded prediction model receives the stylistic feature vector. The trained de-confounded prediction model using the stylistic feature vector generates a prediction value for each of one or more target goals, compares the prediction value for each of the one or more target goals to a target value for each of the one or more target goals and outputs, for display on the GUI, one or more stylistic feature prescriptions to the body of text based on results of the comparing.

Abstract: In one embodiment, a service receives input data from networking entities in a network. The input data comprises synchronous time series data, asynchronous event data, and an entity graph that that indicates relationships between the networking entities in the network. The service clusters the networking entities by type in a plurality of networking entity clusters. The service selects, based on a combination of the received input data, machine learning model data features. The service trains, using the selected machine learning model data features, a machine learning model to forecast a key performance indicator (KPI) for a particular one of the networking entity clusters.

Abstract: A method comprising sending query data representative of a query to a first and second query-answering subsystem of a query-answering system. It is determined that the query-answering system lacks a satisfactory answer to the query. Paraphrase data representative of a rephrased version of the query is received. The paraphrase data is sent to the first and second query-answering subsystems. Answer data representative of an answer to the rephrased version of the query is received from the first query-answering subsystem.

Abstract: A deployment consistency orchestrator includes storage for storing a manual update practice repository and a deployment characteristics repository. The orchestrator further includes an automated update practices manager that identifies a change in update practice event for a deployment; in response to identifying the change in update practice event: identifies, using the deployment characteristics repository, a portion of deployments having a classification that is similar to a classification of the deployment; identifies a portion of the manual update practices repository associated with the portion of the deployments; performs a commonality analysis using the portion of the manual update practices to identify consistent update practices associated with the classification of the deployment; and enforces the consistent update practices associated with the classification on the deployment.

Abstract: A method, system and computer-usable medium are disclosed for updating, upgrading, or performing maintenance on connected devices that includes analyzing usage of the connected devices. A hierarchical representation is formed of the connected devices based on dependency of the devices. Artificial Intelligence/Machine Learning is implemented as to the usage and hierarchical representation to create a model to update or upgrade the connected devices. A schedule is created based on the model that minimizes risk and maximize availability of the connected devices.

Abstract: Systems and methods of adjusting computing device applications, such as smartphone applications, based on external beacon identifiers are described. Based on the identifier of the beacon detected by the smartphone, the smartphone application communicates with a backend server to receive location-specific information based on the identifier of the detected beacon. The location-specific information includes a location-specific user interface. In some arrangements, the location-specific user interface includes a designated user authentication level that varies from other location-specific user interfaces.

Abstract: An approach is provided for automatically generating and processing concept vectors by extracting concept sequences from one or more content sources and generating a first concept vector for a first concept by supplying the concept sequences as inputs to a vector learning component, such that the first concept vector comprises information interrelating the first concept to other concepts in the concept sequences which is inferred from the concept sequences.

Abstract: In data processing device incorporating a processor and memory in communication with the processor, the memory includes executable instructions that, when executed by the processor, cause the data processing device to perform: receiving an attribute metric of a first node with respect to a plurality of second nodes; generating, based on the received attribute metric, a pool of the second nodes that have been in a relationship with the first node; ranking, based on the received attribute metric, the second nodes in the generated pool; dynamically grouping the second nodes to sequentially create one or more level groups; and displaying, on a display, the level groups in a visually differentiated manner reflecting a relative attribute metric of each level group. The device thus presents a display of level groups that is neither cluttered nor sparse.

Abstract: Dynamically routing and re-evaluating a work item based on actions taken on the work item (e.g., adding context information). The augmented routing system categories a work item into one or more dynamic work categories and identifies active knowledge workers and/or knowledge articles based on the work categories. The work item is displayed in a dynamic knowledge worker view, which allows the knowledge worker to take action on the work item. The actions a knowledge worker may take are based on permissions of the knowledge worker, one of the actions that a knowledge worker may take on a work item is to add context information to the work item. After an action is taken on a work item, the system re-evaluates the work item, which may result in the work item being added/removed from one or more work categories; and added/removed from one or more dynamic customized knowledge worker views.

Abstract: Various examples are described for defining automations for client devices enrolled with a management service. A computing environment can cause one or more user interfaces to be shown in a display of an administrator device that include at least one field for receiving a conditional statement to generate an automation associated with client devices enrolled with the management service. The computing environment can validate the conditional statement based on validation criteria and, in an instance in which the conditional statement has been validated, generate the automation based on the conditional statement, the automation causing the computing environment to perform a predetermined action automatically when the conditional statement is satisfied.

Abstract: A method and a system for dynamically modifying at least one element of a User Interface (UI) of a first electronic device are provided. The method includes collating usage information of at least one data source in the first electronic device, categorizing the collated usage information into one or more knowledge clusters, forming a knowledge graph using the one or more knowledge clusters, and dynamically modifying the at least one element of the UI based on the knowledge graph.

Abstract: A system for calculating similarities between drugs and using the similarities to extrapolate side effects of a specified drug comprising: a similarity-computation apparatus configured to use open data to compute similarities between drugs, with: a data integration module configured to obtain data related to a set of drugs from a plurality of open data sources and to integrate the data to generate RDF triples; an RDF module configured to store an RDF graph of the RDF triples: and a similarity calculation module configured to retrieve a list of all the drugs present in the RDF graph and to calculate the similarity of each drug with every other drug in the RDF graph, for storage in a similarity database; and a side effect determining apparatus configured to extrapolate side effects of a specified drug from open data related to the set of drugs, with: a connection to the similarity database; a user interface configured to allow a user to specify a drug from the set of drugs; a neighbours ranking module configure

Abstract: A method, a system and a computer program product for automated ASCII-based object-oriented database schema (OODBS) generation. A parser runs through text sentences of a textual document from a requirements gathering team that includes object-oriented application requirements, and identifies nouns corresponding to an object, and each noun's attributes. An Object-oriented dictionary based ASCII interpreter analyzes the ASCII of the captured requirements. For each identified noun, the system creates first key-value structures mapping each identified object to one or more associated attributes. There is further identified, from the created first key-value structures, any attributes that reference to an identified object, and for each of these identified objects, the system creates second key-value structures mapping, for each attribute identified as a reference, associating a corresponding key where the reference is found as an attribute.

Abstract: Techniques are provided for software license optimization using machine learning-based user clustering. One method comprises obtaining key performance indicators indicating individual usage by a plurality of users of a software product; applying at least one function to the key performance indicators to obtain a plurality of time dependent features; processing the time dependent features using a machine learning model to cluster the users into a plurality of persona clusters; and determining a number of each available license type for the software product for the plurality of users based on the persona clusters. The key performance indicators comprise, for example, user behavioral data with respect to usage of the software product and/or performance data with respect to usage of the software product. One or more policies can be determined for managing an allocation of the available license types for the software product to the plurality of users.

Abstract: A computer-implemented method is provided for managing and sharing picture files. In one embodiment of the present invention, the method comprises providing a server platform and providing a datastore on the server platform for maintaining full resolution copies of the files shared between a plurality of sharing clients. A synchronization engine is provided on the server platform and is configured to send real-time updates to a plurality of sharing clients when at least one of the sharing clients updates or changes one of said files. A web interface may also be provided that allows a user to access files in the datastore through the use of a web browser.

Abstract: Methods for directed analysis of content for storage and recall are performed by systems and apparatuses. The methods optimize search operations for content using a user-driven knowledge bank. A user selects content that is relevant or important to the user for addition to the knowledge bank, and content information about the content is determined based on user importance and context, and is also stored in the knowledge bank. Subsequent searches for the content by the user are optimized based on the content information improving accuracy of search results for the content based on more general queries and searches by the user, including natural language queries and searches. Searches and queries are performed via search engines, as well as digital assistants and search applications of user systems. The content can be added by a user from different applications, and recall of the content from different applications is performed using an API.

Abstract: A system for assisting in diagnosing or troubleshooting an information management system technical problem includes, in some examples, an interface with selectable options, which assist in diagnosing or troubleshooting the technical problem. Via the interface, a software developer or troubleshooting representative can select one or more of the options. For example, a software developer may select an option to automatically receive log data from a component of an information management system that has failed. Other features are also disclosed. The system also comprises functionality for configuring a target system to allow for certain system data about data storage operations to be transmitted to a cloud location from where the data may be accessed for troubleshooting.

Abstract: A computer-implemented method for populating a privacy-related data model by: (1) providing a data model that comprises one or more respective populated or unpopulated fields; (2) determining that at least a particular one of the fields for a particular data asset is an unpopulated field; (3) at least partially in response to determining that the at least one particular field is unpopulated, automatically generating a privacy questionnaire comprising at least one question that, if properly answered, would result in a response that may be used to populate the at least one particular unpopulated field; (4) transmitting the privacy questionnaire to at least one individual; (5) receiving a response to the questionnaire, the response comprising a respective answer to the at least one question; and (6) in response to receiving the response, populating the at least one particular unpopulated field with information from the received response.

Abstract: A workload change evaluator may receive workload metrics characterizing a plurality of workloads executed within a license environment during a license period, and cost metrics characterizing license costs incurred by license environment during the license period. A baseline model generator may generate a baseline model providing a time-based contribution of each of the plurality of workloads to the license cost during the license period. A cost estimator may receive a potential workload change, and may estimate a license cost change caused by the potential workload change, based on the baseline model.

Abstract: A system for providing data security and protection using distributed ledgers to store validated data in a global knowledge graph for fraud detection is disclosed. The system may comprise a data access interface, a processor, and an output interface. The data access interface may receive data associated with an individual from a data source. The processor may convert the data into knowledge graph data by: extracting entities and relations from the data; and translating the data into knowledge graph triples to generate the knowledge graph data. The processor may validate the knowledge graph data using a cryptographic validation, to provide secured contents to update a global knowledge graph to determine a fraudulent activity level associated with the individual based on the updated global knowledge graph. The output interface may transmit a report associated with the fraudulent activity level to a report requestor at a computing device.

Abstract: At least one asset of a given enterprise is identified. The enterprise has a plurality of groups associated therewith. A valuation is computed for the asset using a multi-dimensional model configured to generate cross-group impact values with respect to the asset and two or more of the groups associated with the enterprise. In one example, the multi-dimensional model is in the form of a matrix data structure and the cross-group impact values are off-diagonal entries of the matrix data structure.

Abstract: The present invention includes a computing device that may receive a business problem in a natural language. The computing device may determine a domain classification from the business problem, where the domain classification is a list of domains determined from an application programming interface (API) catalog. The computing device may generate a problem graph from the business problem, where the problem graph is a parsed tree of natural language elements extracted from the natural language and stored as a database. The computing device may retrieve one or more assets from the plurality of assets based on the domain classification and the problem graph. The computing device may generate a problem-solution graph from the one or more assets and generate a solution API pipeline graph for evaluation by a user and compilation by a pipeline assembler.

Abstract: Probable origination date may be derived by using a stream of data captured, for example, from the Internet and from other documentation sources such as historical information about a target object, its author, related environmental data, social media data, blogs, microblogs, posts, historical information, and/or other data sources. Techniques such as textual analysis, statistical analytics, and/or artificial intelligence may combine and correlate the information from data sources to extract clues that may indicate the original author and date of authorship. Based on the number of conflicting or validating references, and the relationships between them, a probability or confidence score in the accuracy of the analysis may be generated.

Abstract: Probable origination date may be derived by using a stream of data captured, for example, from the Internet and from other documentation sources such as historical information about a target object, its author, related environmental data, social media data, blogs, microblogs, posts, historical information, and/or other data sources. Techniques such as textual analysis, statistical analytics, and/or artificial intelligence may combine and correlate the information from data sources to extract clues that may indicate the original author and date of authorship. Based on the number of conflicting or validating references, and the relationships between them, a probability or confidence score in the accuracy of the analysis may be generated.