Abstract: Tabular data is accessed that contains multiple entries of alphanumeric data. Multiple tokens are generated of the multiple entries of alphanumeric data using a tokenization process. The tokenization process maintains jargon-specific features of the alphanumeric data. Multiple embeddings of the multiple entries of alphanumeric data are generated using the tokens. The embeddings capture similarity of the multiple entries considering all of global features, column features, and row features in the tokens of the tabular data. A neural network is used to predict probabilities for pre-defined classes for the tabular data using the generated embeddings.

Abstract: Systems, computer program products, and methods are described herein for implementing natural language processing to determine natural language from computer programming language in an electronic environment.

Abstract: Detecting and mitigating anomalous system behavior by providing a machine learning model comprising a knowledge graph depicting system entity relationships, and modeling behavioral correlations among system entities according to historical time-series data, receiving real-time time-series data for the system, detecting an anomalous system behavior in a system locale, according to the real-time time-series data, according to the machine learning model and multivariate sensor metrics, diagnosing the anomalous system behavior according to an upstream portion of the knowledge graph and a statistical behavior model for the system locale, and mitigating the anomalous behavior by deriving a recommended action according to the anomalous behavior and generating a work order to implement the recommended action.

Abstract: Various systems and methods are presented regarding code-based pattern extraction (Code-PE) and the application of Code-PE to a named entity recognition pipeline. Patterns can be generated from named entities, wherein the entities have an assigned type. Codes are identified within the entities, subsequently vectorized and clustered based upon the presence of the identified codes. Patterns are identified for the respective clusters. The patterns can be applied to an untyped entity, in the event of the pattern matching, the entity can be typed with the type assigned to the pattern. The typed entity can be used to recursively update knowledge regarding typed- and untyped-entities. In the event a pattern incorrectly types an entity, the pattern can be retrained with the updated knowledge.

Abstract: Users of an endpoint remediation system can be assigned to different roles, from which they can request exceptions, approve exceptions, and/or enable remediation on endpoint devices. The compliance scanning and enforcing process can be automated, while allowing entities to request and/or approve certain exceptions. Therefore, security compliance for customers can be actively managed to provide visibility to the endpoint device compliance state at any time.

Abstract: Embodiments of the invention are directed to a computer-implemented method. A non-limiting example of the computer-implemented method includes accessing, using a processor system, a process-step sequence that includes a plurality process-steps and a plurality of queue-times. A process-step sequence mining operation is applied to the process-step sequence, wherein the process-step sequence mining operation is operable to make a prediction of an impact of a portion of the process-step sequence on a characteristic of a product generated by the process-step sequence.

Abstract: Tabular data is accessed that contains multiple entries of alphanumeric data. Multiple tokens are generated of the multiple entries of alphanumeric data using a tokenization process. The tokenization process maintains jargon-specific features of the alphanumeric data. Multiple embeddings of the multiple entries of alphanumeric data are generated using the tokens. The embeddings capture similarity of the multiple entries considering all of global features, column features, and row features in the tokens of the tabular data. A neural network is used to predict probabilities for pre-defined classes for the tabular data using the generated embeddings.

Abstract: Users of an endpoint remediation system can be assigned to different roles, from which they can request exceptions, approve exceptions, and/or enable remediation on endpoint devices. The compliance scanning and enforcing process can be automated, while allowing entities to request and/or approve certain exceptions. Therefore, security compliance for customers can be actively managed to provide visibility to the endpoint device compliance state at any time.

Abstract: Temporal and spatially integrated forecast modeling includes generating a plurality of forecast models for a plurality of short-term to long-term time periods for a plurality of locations. Temporally integrating the plurality of forecast models sequentially over the plurality of time periods for the plurality of locations and spatially integrating the temporally integrated plurality of forecast models for each location hierarchically over the geographic areas. The forecast models are autoregressive distributed lag models with different explanatory variables for the short-term and long-term forecast models. The temporally integrating includes recursively integrating the plurality of forecast models over the time periods from the short-term to the long-term time periods and the spatially integrating includes recursively integrating the temporally integrated plurality of forecast models hierarchically from larger size geographic areas to smaller size geographic areas.

Abstract: A concept associated with a feature used in machine learning model can be determined, the feature extracted from a first data source. A second data source containing the concept can be identified. An additional feature can be generated by performing a natural language processing on the second data source. The feature and the additional feature can be merged. A second machine learning model can be generated, which use the merged feature. A prediction result of the first machine learning model can be compared with a prediction result of the second machine learning model relative to ground truth data, to evaluate effective of the merged feature. Based on the evaluated effectiveness, the feature can be augmented with the merged feature in machine learning.

Abstract: Users of an endpoint remediation system can be assigned to different roles, from which they can request exceptions, approve exceptions, and/or enable remediation on endpoint devices. The compliance scanning and enforcing process can be automated, while allowing entities to request and/or approve certain exceptions. Therefore, security compliance for customers can be actively managed to provide visibility to the endpoint device compliance state at any time.

Abstract: Users of an endpoint remediation system can be assigned to different roles, from which they can request exceptions, approve exceptions, and/or enable remediation on endpoint devices. The compliance scanning and enforcing process can be automated, while allowing entities to request and/or approve certain exceptions. Therefore, security compliance for customers can be actively managed to provide visibility to the endpoint device compliance state at any time.

Abstract: A method is provided for creating a semantic model for submitting search queries thereto. The method includes an act of receiving data from one or more input sources in an entity and relationship capture service of a situational awareness engine. The method further includes an act of extracting entities and relationships between the entities in two or more extraction services, where the two or more extraction services include at least two of a table-to-graph service, an event-to-graph service, a sensor-to-graph service, a text-to-graph service, and an image-to-graph service. The method includes an act of generating a semantic model based on fusion and labeling the extracted data provided by the at least two extraction services, where the semantic model can receive a search query and respond to the search query based on the generated semantic model.

Abstract: Content is selectively provided to users of mobile devices within a venue including an on-site wireless network. User authorization requests and/or user account registration data are transmitted to the on-site wireless network from mobile devices within the venue. Attributes such as user interests and professions, which comprise inferred user profiles, are obtained using the network traffic data. Identities of mobile devices are established based on a combination including two or more of network identifiers, mobile device signatures, and browser signatures. The inferred user profiles are correlated with the mobile device identities. The inferred user profiles are aggregated into user profile groups and then matched with a content provider's intended target profiles. Content is transmitted to the mobile devices corresponding to the intended target profiles and based on correlation of the inferred user profiles with identities of the devices.

Abstract: Providing real-time awareness of an audience to a presenter during the presentation. In response to presenting a presentation to an audience, information is automatically collected about the audience from sensors positioned amongst the audience. The collected information about the audience is analyzed and, during the presentation, recommendations are made to the presenter for improving the presentation based on the collected information.

Abstract: Providing real-time awareness of an audience to a presenter during the presentation. In response to presenting a presentation to an audience, information is automatically collected about the audience from sensors positioned amongst the audience. The collected information about the audience is analyzed and, during the presentation, recommendations are made to the presenter for improving the presentation based on the collected information.

Abstract: Users of an endpoint remediation system can be assigned to different roles, from which they can request exceptions, approve exceptions, and/or enable remediation on endpoint devices. The compliance scanning and enforcing process can be automated, while allowing entities to request and/or approve certain exceptions. Therefore, security compliance for customers can be actively managed to provide visibility to the endpoint device compliance state at any time.

Abstract: Content is selectively provided to users of mobile devices within a venue including an on-site wireless network. User authorization requests and/or user account registration data are transmitted to the on-site wireless network from mobile devices within the venue. Attributes such as user interests and professions, which comprise inferred user profiles, are obtained using the network traffic data. Identities of mobile devices are established based on a combination including two or more of network identifiers, mobile device signatures, and browser signatures. The inferred user profiles are correlated with the mobile device identities. The inferred user profiles are aggregated into user profile groups and then matched with a content provider's intended target profiles. Content is transmitted to the mobile devices corresponding to the intended target profiles and based on correlation of the inferred user profiles with identities of the devices.

Abstract: Content is selectively provided to users of mobile devices within a venue including an on-site wireless network. User authorization requests and/or user account registration data are transmitted to the on-site wireless network from mobile devices within the venue. Attributes such as user interests and professions, which comprise inferred user profiles, are obtained using the network traffic data. Identities of mobile devices are established based on a combination including two or more of network identifiers, mobile device signatures, and browser signatures. The inferred user profiles are correlated with the mobile device identities. The inferred user profiles are aggregated into user profile groups and then matched with a content provider's intended target profiles. Content is transmitted to the mobile devices corresponding to the intended target profiles and based on correlation of the inferred user profiles with identities of the devices.

Abstract: A method and system of characterizing a job market is provided. The available job postings of a job market are determined. For each job posting, one or more technical skills, a job role level, and one or more professional capabilities related to the job posting are determined. The professional capabilities are aggregated by job dimensions. The determined technical skills and the professional capabilities of each job posting and the aggregated professional capabilities are stored in a database as reference data. A job capability profile for one or more job dimensions is provided based on the stored reference data in the database.