Abstract: A computer-implemented system and method for a data leakage and misuse detection system comprises receiving an evaluation dataset A, and building a signature of the evaluation dataset A (sig(A)), where A signature of a dataset is a multi-level evaluation data abstraction representation of the dataset. The method further comprises building a signature for each of existing datasets B (B1, B2, . . . , Bn) (sig(Bx)) that are stored in a memory. The method then compares the sig(A) with each of the sig(Bx)s. A similarity score is derived based on the comparing, and responsive to determining the similarity score exceeds a predefined threshold, the method comprises generating an activity related to the determination.

Abstract: A computer-implemented method, a computer system and a computer program product enhance multimedia quality. The method includes receiving a plurality of sequential frames of a scene in a video. The method also includes generating dataframes for current frames and for a reference frame of the video. The method further includes comparing the dataframes for the reference and current frames. In addition, the method includes determining a quality metric of the current frames based on the comparison of the dataframes for the reference and current frames. The method also includes determining if the quality metric can be improved by altering the video in response to determining that the quality metric of one of the current frames is below a threshold. Finally, the method includes inserting expansion frames into the video in response to determining that the quality metric can be improved by altering the video.

Abstract: A computer-implemented method, a computer system and a computer program product improve the quality of multimedia. The method includes displaying a current frame of a video. The method also includes generating dataframes for the current frame and for a reference frame of the video. The method further includes comparing the dataframes for the reference and current frames. In addition, the method includes determining a quality metric of the current frame based on the comparison of the dataframes for the reference and current frames. Finally, the method includes altering an orientation of the display of the current frame in response to determining that the quality metric of the current frame is below a threshold.

Abstract: A computer-implemented method, a computer system and a computer program product evaluate multimedia quality. The method includes displaying a current frame of a video. The method also includes generating dataframes for the current frame and for a reference frame of the video. The method further includes comparing the dataframes for the reference and current frames. In addition, the method includes determining a quality metric of the current frame based on the comparison of the dataframes for the reference and current frames. Finally, the method includes modifying the current frame so that the quality metric is at or above the threshold in response to determining that the quality metric of the current frame is below a threshold.

Abstract: One embodiment of the invention provides a method for utility-preserving text de-identification. The method comprises generating corresponding processed text for each text document by applying at least one natural language processor (NLP) annotator to the text document to recognize and tag privacy-sensitive personal information corresponding to an individual, and replacing some words in the text document with some replacement values. The method further comprises determining infrequent terms occurring across all processed texts, filtering out the infrequent terms from the processed texts, and selectively reinstating to the processed texts at least one of the infrequent terms that is innocuous.

Abstract: The present disclosure provides for medical device administration and interaction by identifying a medical event affecting a first individual, a medical device associated with treating the medical event, and an initial attentiveness level of an administering individual; outputting a tutorial for how to use the medical device to treat the medical event with a first control level, wherein the first control level based on the initial attentiveness level of the administering individual; and in response to receiving a triggering event while outputting the tutorial: determining a current attentiveness level for the administering individual; and in response to the current attentiveness level indicating a change from the initial attentiveness level, adjusting the tutorial based on a second control level, different than the first control level, based on the change from the initial attentiveness level.

Abstract: A baseline of behavior is determined for a population of users that interact with an autonomous agent that is configured to respond to natural language prompts of users of the population using respective user profiles for each user. An element associated with a first user that deviates more than a threshold amount from the baseline is identified. In response to the element deviating more than the threshold amount, the autonomous agent is caused to engage the first user unprompted regarding the element via an engagement that is configured to verify an association between the first user and the element. A response from the first user regarding the engagement is determined to verify the association between the first user and the element. A first user profile that corresponds to the first user is updated in response to determining that the first user response verifies the association.

Abstract: A system and method for assessing a potential problem associated with information in a document. In an embodiment, a document for analysis may be received, the document being part of a corpus of one or more documents stored in an electronic format. The document may be analyzed to identify reference(s) in the document, wherein the reference(s) are each selected from the group comprising a natural language statement, a reference in a first part of the document to a second part of the document, or a reference to or from another document. Based on the reference(s), a knowledge graph may be generated to represent information in the document. A risk assessment of a reference in the document may be determined using the knowledge graph. A visual indicator may be applied to the document that emphasizes a potential problem with the reference based on the risk assessment.

Abstract: Software application data management. A data stream generated via a software application is received. A user profile is determined for a developer of the software application. One or more complications in a data model of the software application are predicted. Data of the data stream received is managed based on the one or more complications in the data model.

Abstract: A method, computer system, and a computer program product for recommending additional content to an author generating authored content is provided. The present invention may include monitoring a travel location associated with the author. The present invention may include calculating a multi-sensory region based on the travel location and a maximum sense distance value. The present invention may include selecting at least one piece of additional content from a corpus of additional content based on the multi-sensory region. The present invention may include generating a model based on the at least one piece of additional content. The present invention may include selecting a relevant piece of additional content from the data model based on determining a topic associated with the relevant piece of additional content matches an authored topic associated with the authored content. The present invention may include presenting the selected relevant piece of additional content to the author.

Abstract: Software application data management. A data stream generated via a software application is received. A user profile is determined for a developer of the software application. One or more complications in a data model of the software application are predicted. Data of the data stream received is managed based on the one or more complications in the data model.

Abstract: An embodiment trains a machine-learning model using a first training corpus of general items indicative of varying levels of confidence. The embodiment also prepares a second training corpus that includes domain-specific items indicative of varying levels of confidence extracted from communications from members of a project group associated with a project. The embodiment retrains the machine-learning model using the second training corpus and generates a confidence score for the project based on confidence values assigned by the machine-learning model to each of a plurality of project-related communication items from members of the project group. The embodiment also detects that the confidence score is below a predetermined threshold confidence level and, in response, initiates a communication to members of the project group conveying information regarding an automated remedial action for the project.

Abstract: Dynamically moderating healthcare application data. Receive an incoming data load request comprising a plurality of referential data elements and assess a downstream query impact of the plurality of referential data elements. Determine, based on the assessing, a sensitivity level of the plurality of referentoial data elements, and alter, based on the sensitivity level, compilation of insights generated using the plurality of referential data elements and compilation of a plurality of referenced data elements.

Abstract: Provided are techniques for alert generation based on a cognitive state and a physical state. Wearables data, text communications, voice communications, and images of a caregiver providing care to a patient are obtained. The wearables data, the text communications, the voice communications, and the images are analyzed to identify a cognitive state and a physical state of the caregiver. The cognitive state and the physical state are compared to one or more care rules associated with tasks of the caregiver for the patient. In response to the comparison indicating any one of the cognitive state and the physical state prevent the caregiver from executing the tasks, an alert is generated. One or more recommendations for resolving the alert based on one or more recommendation rules are generated.

Abstract: Systems and techniques that facilitate quantum circuit valuation are provided. In various embodiments, a system can comprise an input component that can access a first quantum circuit. In various embodiments, the system can further comprise a valuation component that can appraise the first quantum circuit based on one or more factors (e.g., frequency factor, complexity factor, resource factor, similarity factor), thereby yielding a value score that characterizes the first quantum circuit. In various instances, the system can further comprise an execution component that can recommend deployment of the first quantum circuit based on determining that the value score exceeds a threshold.

Abstract: Aspects of the invention include receiving a data erasure request associated with a user and identifying, based at least in part on the data erasure request, an entity associated with the user and one or more identifiers for the user. Aspects also include identifying, based at least in part on the one or more identifiers for the user, a cohort that includes the user and comparing the one or more identifiers for the user to identifiers of a plurality of users that are not members of the cohort. Aspects further include identifying a replacement user from the plurality of users based on the comparison and replacing the entity associated with the user in the cohort with an entity associated with the replacement user.

Abstract: Aspects of the invention include receiving, by a processor, medical data associated with a patient, populating a patient ontology for the patient with the medical data, determining a completeness the patient ontology for the patient based at least in part on the medical data, querying an upstream data source based on the completeness of the patient ontology, updating the patient ontology based on a query response from the upstream data source, analyzing the updated patient ontology to determine an insight for the patient, and enacting an action based on the insight for the patient.

Abstract: Examples described herein provide a computer-implemented method that includes scanning, by a processing device, a code dependency list and a hierarchy of a core code component. The method further includes pulling, by the processing device, data of the core code using the scanned code dependency list. The method further includes extracting, by the processing device, information from the data for each dependency. The method further includes scoring, by the processing device, the information between versions to detect a likelihood of user data posture changes. The method further includes enforcing, by the processing device, a compensating control for the core code.

Abstract: Confusion reduction in an online social network. A method identifies elements in social media message content, determines, based on the identified elements, a plurality of candidate audiences to which the social media message content is potentially targeted, indicates, to a user, the plurality of candidate audiences and suggested additional elements to apply to the social media message content to tailor the social media message content to a target audience of the plurality of candidate audiences, and modifies the social media message content with one or more additional elements of the suggested additional elements, the modifying adding the one or more additional elements to the social media message content and targeting the social media message content to the target audience.

Abstract: A method, system, and computer program product to prevent misinterpretation of communications via artificial intelligence assistants. The method includes monitoring an artificial intelligence enabled communication. The method also includes analyzing messages, participants, and actions within the communication. The method also includes identifying critical data within the communication. The method also includes determining critical sequence data, where the critical sequence data is a sequence of conversation elements that contains the critical data. The method also includes predicting an uncertainty level for the critical sequence data, where the uncertainty level indicates an amount of uncertainty that the artificial intelligence correctly interprets the critical sequence data. The method also includes determining that the uncertainty level for the critical sequence data is above a threshold uncertainty value, resulting in critical sequence data that is subject to misinterpretation.