Abstract: Chat discourse convolution can include performing a lexicographic analysis of the content of a chat message of a chat discourse and storing a result of the lexicographic analysis in a database. The convolution can further include generating a hash of the content of the chat message and generating a leximarker. The leximarker can encapsulate a reference to the stored lexicographic analysis as well as the hash of the content of the chat message.

Abstract: A system, method and computer program product for cognitive copy and paste. The method includes: receiving, at a hardware processor of a computer system, an input representing a selection of a content captured from a source application program, and receiving an input representing an identified target application program that will receive the selected content to be copied and rendered in the target application program. The selected content is analyzed to determine a context for the selected content; and a rendering of the selected content at a location within the destination application based on the determined context, the rendering achieving a best representation of the selected content on the destination application. The analyzing includes invoking a natural language processor to determine an intent, meaning, or an intended use of the selected content based on the determined context, and employs a support vector machine for determining a best format change when rendering.

Abstract: A blockchain of transactions may be referenced for various purposes and may be later accessed by interested parties for ledger verification. One example operation may comprise one or more of identifying determining a shared file is being edited by one or more entities, identifying one or more changes to the shared file while the shared file is being edited, signing the one or more changes with one or more public keys, and adding the one or more changes to a blockchain.

Abstract: A method, system and computer program product for providing enhanced action fulfillment using classification valency. At least a first message from a user in a channel is analyzed, the first message containing first data of a first data type, and a classification of the first message is inferred based on the first data's content. At least a second message from the user in the channel is analyzed, the second message containing second data of a second data type different from the first data type, and a classification model of the second message is derived based on the second data's content. The classification of the first message and the classification model of the second message are used to determine whether an additional inference is available based on the classification valency. The additional inference is incorporated to determine the enhanced action fulfillment, and the enhanced action is presented to the user for fulfillment.

Abstract: Active speaker detection can include receiving speaker detection signals from a plurality of devices participating in an electronic meeting. Each speaker detection signal specifies a score indicating whether an active speaker is detected by a respective device of the plurality of devices that generates the speaker detection signal. Active speaker detection further can include determining, using a processor, a device of the plurality of devices that detects an active speaker based upon the speaker detection signals, wherein, in response to the determining, the method further comprises: providing video received from the determined device to the plurality of devices during the electronic meeting.

Abstract: A computer implemented method for managing wireless bands and/or wireless channels comprises receiving information on connected local devices for a plurality of wireless routers, wherein the plurality of wireless routers are using a same wireless band and/or wireless channel, and wherein each connected local device for which information is received utilizes one or more of the plurality of wireless routers for a network connection. The method further comprises calculating, for each of the plurality of wireless routers, a congestion quotient from the received information on the connected local devices, wherein the congestion quotient defines a likelihood of destructive interference at each respective wireless router. The method further comprises determining changes in wireless band and/or wireless channel for one or more wireless routers of the plurality of wireless routers, wherein the changes lower the respective congestion quotients for each of the respective one or more wireless routers.

Abstract: A method, a device and a computer program product for processing a segment are proposed. In the method, a property of at least one of a first segment and a second segment in a segment set is obtained. The segment set includes a plurality of segments belonging to at least one conversation. The second segment occurs after the first segment. A boundary feature of at least one of the first segment and the second segment is determined based on the property. The boundary feature indicates whether there is a boundary of a conversation after the first segment.

Abstract: Familiarity-based text classification framework selection is described. A list of participants in an electronic message thread is selected. For each pairing of participants, a familiarity score is determined based on a number of criteria. A familiarity model is formed based on multiple familiarity scores and a text classification framework for the electronic message thread is selected based on the familiarity model.

Abstract: A computer-implemented method includes: generating, by a computer device, a baseline emotive state of a first user; generating, by the computer device, a baseline emotive state of a second user; determining, by the computer device, a current emotive state of the first user during a current video conference between the first user and the second user; determining, by the computer device, a current emotive state of the second user during the current video conference; and suggesting, by the computer device, a behavioral adjustment to the first user based on comparing the baseline emotive state of the first user, the current emotive state of the first user, the baseline emotive state of the second user, and the current emotive state of the second user.

Abstract: User activity pertaining to a product is automatically analyzed. Based, at least in part, on the analyzing the user activity pertaining to the product, a temporal logging level model can be derived. The temporal logging level model can determine a first logging level to be applied to the product. The temporal logging level model also can determine a duration of time for which the first logging level is to be applied to the product. Application of the first logging level to the product for the determined duration of time can be initiated.

Abstract: A set of data comprising heterogeneous data is processed in accordance with a data clustering algorithm so as to obtain an initial data cluster comprising homogeneous data. A supervised data cluster generated based on a human analysis of the set of data is obtained and compared with the initial data cluster to obtain a comparison result. The data clustering algorithm is modified based on the comparison result.

Abstract: Modification of a user skill profile based upon social presence includes receiving a document indicating skill competencies of a user, and analyzing the document to determine a first model. The first model includes skill competencies indicated within the document. A social media profile associated with the user is received. The social media profile is analyzed to determine a second model. The second model includes current skills competencies of the user indicated by the social media profile. The first model and the second model is compared to determine missing skill competencies, the missing skill competencies including current skill competencies in the second model that are missing from the document. The document is modified to include the missing skill competencies.

Abstract: Various embodiments for managing dialog comments by a processor are provided. Each communication of a dialog communicated by one or more users using one of a plurality of applications may be monitored, tracked, and/or analyzed using a machine learning operation and/or a natural language processing operation. A topic trajectory of the dialog may be identified between one or more users using one of a plurality of applications. A selected comment submitted by the one or more users may be automatically transformed according to one or more corrective actions upon the selected communication deviating from the topic trajectory.

Abstract: A method, system and computer program storage device to assist users interacting with message threads on social media. In an embodiment, the method comprises monitoring a message thread comprised of messages among a group of users on a social media platform for content that is inflammatory to one of the users; and when the inflammatory content has a defined condition, preventing the one of the users from posting messages to the message thread for a specified length of time. In an embodiment the defined condition is a defined level of the inflammatory content in the thread. In an embodiment, the defined condition is a defined increasing trend of the inflammatory content in the thread. In an embodiment, the monitoring the thread includes categorizing potentially inflammatory content into a plurality of categories, and specifying an inflammatory content level for each of the categories.

Abstract: Micro-term modeling for chat discourse includes determining, using computer hardware, a role of a user and a domain of reference of the user based on electronic chat messages for the user across a plurality of group chats, determining, using the computer hardware, topics from a selected group chat in which the user is a participant, determining, using the computer hardware and from the selected group chat, a segment of interest to the user based on the role, the domain of reference, and the topics found in the selected group chat, and providing, using the computer hardware, an indicator of the segment of interest.

Abstract: Identification of content classes deemed important by users is received. Classifiers are trained on user communication text to recognize content matching content classes. A composite classifier is applied to text of communication among users of a second set of users, including tagging, by the composite classifier, content in text of communication among the users of the second set. The tagging is responsive to the classifiers recognizing their respective content classes in text of communication among the users of the second set.

Abstract: Systems and methods for communication inversion for online communities are disclosed. In embodiments, a computer-implemented method comprises: detecting, by a computing device, that an online community has a low vitality; determining, by the computing device and based on the detecting that the online community has a low vitality, a related community is associated with the online community; detecting, by the computing device, a participant communication within the related community; and redirecting, by the computing device, the participant communication to the online community.

Abstract: A thread delta prediction and cognitive conversation opportunity generation. A prediction model may be generated based on chat space conversation data, and predicts a chat thread delta associated with a current chat conversation data. A data package may be created based on the chat thread delta. Based on the data package, a conversation opportunity may be determined for a given topic for given user in the chat space, to conduct during a time period of the chat thread delta in real-time.

Abstract: Methods and systems for leveraging a topic divergence model to generate dynamic sidebar chat conversations are disclosed. A method includes: collecting, by a computing device, data from a first group chat; determining, by the computing device, a main topic of the first group chat and a current topic of the first group chat using the data collected from the first group chat; determining, by the computing device, a first divergence score representing a degree of divergence between the main topic of the first group chat and the current topic of the first group chat; determining, by the computing device, that the first divergence score exceeds a predetermined threshold; and in response to determining that the first divergence score exceeds the predetermined threshold, the computing device creating a second group chat; determining an efficacy based on an emotive analysis which increases as the divergence score decreases.

Abstract: A method, computer program product, and system for tracking scheduled and unscheduled tasks of devices in case of an electrical power outage is provided. The method includes providing a hub connected to an electrically powered device, where the hub is powered by an uninterruptible power source. The method further includes continually recording data regarding the operational state of the electrically powered device using one or more sensors attached to the electrically powered device. The method further includes tracking progress of tasks associated with the electrically powered device, based on the continual recording of data regarding the operational state of the electrically powered device. The method further includes, upon detecting a power outage followed by a restore of power, identifying an expected activity to resume a task associated with the electrically powered device, based on the tracked progress of the task prior to the power outage.