Abstract: Systems and methods of the invention determine evasiveness of postings and manage chat sessions accordingly. In embodiments, a method includes accessing a real-time text-based discourse session comprised of multiple text-based posts published by participants, the posts including a question from an author and responses from at least one respondent; determining relationships between words in the text-based discourse session utilizing corpus linguistics analysis; determining a frequency of the responses of the at least one respondent over time; determining an evasiveness score for each of the responses based on natural language processing of the responses, wherein each of the evasiveness scores indicate a level of relevance of a response with respect to the question; determining rankings for each of the responses based on the determined relationships of words, the frequency of the responses, and the evasiveness scores; and determining a display order for the responses based on the rankings of the responses.

Abstract: A method for adjusting an on-screen virtual keyboard on a computer device is provided. The method may include determining user hand and finger movement in relation to the on-screen virtual keyboard on the computer device. The method may further include determining a user chat discourse based on information associated with a chat interface on the computer device. The method may further include generating a programmatic model that combines and correlates the determined user hand and finger movement on the on-screen virtual keyboard with the determined user chat discourse. The method may further include dynamically adjusting an on-screen virtual keyboard layout associated with the on-screen virtual keyboard using the programmatic model, wherein dynamically adjusting the on-screen virtual keyboard layout comprises adjusting one or more keys on the on-screen virtual keyboard in response to information associated with a user and the chat interface.

Abstract: Participant inclusion determination can include generating a textual analysis of a draft of an electronic communication in response to a sender preparing the draft for conveyance over an electronic communications network. A word relevance score can be computed for each word of the draft based on the textual analysis. Probabilistically weighted distances between the sender, an initial recipient of the electronic communication, and more additional recipient candidates for additionally receiving the electronic communication can be determined. The probabilistically weighted distances can correspond to hierarchical distances within a hierarchical structure corresponding to an organization in which the sender, the initial recipient, and one or more additional recipient candidates are members.

Abstract: Participant inclusion determination can include generating a textual analysis of a draft of an electronic communication in response to a sender preparing the draft for conveyance over an electronic communications network. A word relevance score can be computed for each word of the draft based on the textual analysis. Probabilistically weighted distances between the sender, an initial recipient of the electronic communication, and more additional recipient candidates for additionally receiving the electronic communication can be determined. The probabilistically weighted distances can correspond to hierarchical distances within a hierarchical structure corresponding to an organization in which the sender, the initial recipient, and one or more additional recipient candidates are members.

Abstract: Bystander effect management can include determining a likelihood of a bystander effect on at least one chat participant engaging in a chat discourse over an electronic communications network. The likelihood can be determined by a bystander effect perception (BEP) model generated based on collaboration interaction metrics derived from prior discourses conducted over the electronic communications network by a chat group. A bystander effect reaction (BER) can be generated in response to determining that the likelihood of the bystander effect exceeds a predetermined threshold, the BER being determined based on the BEP model to be more likely than not to enhance collaboration among at least some chat participants engaging in the chat discourse. A notification based on the BER can be conveyed to one or more chat participants engaging in the chat discourse over the electronic communications network.

Abstract: A discourse pattern is generated by analyzing a set of natural language interactions. A sensor activation plan corresponding to the discourse pattern is determined, the sensor activation plan comprising a data collection parameter corresponding to a first sensor. Within a first natural language interaction, a first pattern having above a threshold similarity to the discourse pattern is detected. Responsive to the detecting, a configuration of the sensor is adjusted according to the sensor activation plan.

Abstract: The exemplary embodiments disclose a system and method, a computer program product, and a computer system for managing the distinctiveness of multimedia. The exemplary embodiments may include detecting an input of multimedia data, extracting one or more features from the multimedia data, and determining a distinctiveness of the multimedia based on applying one or more models to the extracted one or more features.

Abstract: A method, computer system, and computer program product for petition creation through social analytics are provided. The embodiment may include generating a repository of user social data. The embodiment may also include extracting one or more social topics that are related to the user social data. The embodiment may further include generating a social supplication model using the repository and the extracted social topic. The embodiment may also include determining discussion issues within the social topic and a topic discussion distance between each user based on the generated social supplication model. The embodiment may further include generating a petition based on a determined discussion issue.

Abstract: A computer-implemented method and system for arranging, in an ordered hierarchy, attached files as transferred during a discourse history. The computer implemented method includes accessing discourse data associated with a history of discourse communications. In embodiments, the discourse data includes a plurality of discourse attachments transferred in accordance with the history, and the discourse attachments include multiple versions of at least one discourse attachment within the plurality. The method further includes deriving a discourse attachment arrangement (DAA) component based at least in part on the discourse data. The method includes outputting, based at least in part on the DAA component, the multiple versions of the at least one discourse attachment arranged in a hierarchical order.

Abstract: The exemplary embodiments disclose a system and method, a computer program product, and a computer system for managing the distinctiveness of multimedia. The exemplary embodiments may include detecting an input of multimedia data, extracting one or more features from the multimedia data, and determining a distinctiveness of the multimedia based on applying one or more models to the extracted one or more features.

Abstract: A method, a computer system, and a computer program product for managing content relevancy is provided. Embodiments of the present invention may include collecting and analyzing a plurality of data, wherein the plurality of data includes document data, document access data and user data. Embodiments of the present invention may include retrieving topic model content based on the plurality of data. Embodiments of the present invention may include building a machine learning (ML) model to determine one or more topics contained in the topic model content. Embodiments of the present invention may include generating a heatmap based on the user data. Embodiments of the present invention may include building a content relevancy model (CRM) based on the ML model and the heatmap. Embodiments of the present invention may include determining an action state for the document data. Embodiments of the present invention may include storing the CRM.

Abstract: The exemplary embodiments disclose a system and method, a computer program product, and a computer system for scheduling calendar events. The exemplary embodiments may include collecting data and identifying one or more factors from the collected data. The exemplary embodiments may additionally include scheduling the one or more calendar events by applying one or more models to the identified one or more factors.

Abstract: In an approach, a processor detects at least one training message delivered by a user on a social media application, the training message being accessible by an operator. A processor records training feedback performed by the operator on the social media application regarding to the at least one training message. A processor trains an analysis engine module using (i) the at least one training message as input and (ii) the training feedback as output. A processor generates a predicted feedback for a subsequent message based on the trained analysis engine module.

Abstract: A set of ticket transfer data associated with a user is monitored. A user profile to store the set of ticket transfer data is generated. A risk score for the user is calculated, based on the user profile. A ticket transfer attempt by the user is detected. Based on the risk score, the ticket transfer attempt is determined to meet a set of transfer criteria. The ticket is posted for transfer, and the user profile is updated, according to the ticket transfer attempt.

Abstract: In an approach to training a corpus link model and generating collocated terms for intra-channel and inter-channel activity, one or more computer processors train a corpus link model based on an analysis of a linguistic corpus and an analysis of one or more author metrics. The one or more computer processors generate one or more collocated terms based on one or more calculations by the trained corpus link model. The one or more computer processors generate a co-occurrence rating for each of the one or more generated collocated terms. The one or more computer processors display the one or more generated collocated terms according to the generated co-occurrence rating of each collocated term.

Abstract: A method, system, and computer program product for creating step-based answers from multimedia content are provided. The method receives a search query including a set of search terms. A set of question characteristics is determined for the search query. The set of question characteristics are based in part on the set of search terms. The method generates a set of steps for an answer to the search query. The set of steps are generated based in part on the set of question characteristics. The method identifies media content relevant to the set of steps and segments the media content to generate a set of media segments. Each media segment of the set of media segments represent a portion of the media content. The method combines the set of media segments based on the set of steps to generate a media answer to the search query.

Abstract: According to one embodiment, a method, computer system, and computer program product for detecting and repairing gaps within a call is provided. The present invention may include requesting a personal discourse gap recovery model (PDGRM) for participants in a call, where the PDGRM may be a machine learning model that models a user's speech patterns based on word collocation, dictionary, and speaking rate. The present invention may further comprise detecting one or more gaps in the call based on network connectivity, inserting an audio delay into the call, constructing repaired dialogue to fill at least one of the one or more gaps in the call based on the PDGRM, and inserting the repaired dialogue into the call.

Abstract: A method, computer system, and computer program product for collaborative document relations modeling are provided. The embodiment may include parsing, by a processor, content of a web conference recording document utilizing multi-modal analysis. The embodiment may also include deriving a social meeting bookmark model based on the multi-modal analysis to combine results of the multi-modal analysis into a matrix. The embodiment may further include generating bookmarks of the parsed content based on the derived social meeting bookmark model and the matrix. The embodiment may also include storing the bookmarks and the social meeting bookmark model in a database.

Abstract: One embodiment of the present invention provides a method comprising running a monitoring agent on a connected electronic device, and determining, via the monitoring agent, a level of hearing impairment of an individual user associated with the connected electronic device. The method further comprises, in response to determining the individual user has some level of hearing impairment, selecting a notification mechanism suitable for notifying the individual user based on the level of hearing impairment, and invoking the monitoring agent to notify the individual user of an event in accordance with the notification mechanism selected.

Abstract: Providing learned interactions in a virtual reality or augmented reality (collectively, a computer-mediated reality) can include determining a probable physical action of a user interacting with a computer-mediated reality (CMR) environment. A learned interaction corresponding to the probable physical action can be generated based on a CMR-physical action (CMRPA) model that correlates physical actions with results of the physical actions in a CMR scenario of the CMR environment. In response to determining, based on at least one identified characteristic of the user, a statistical likelihood of benefiting the user by providing the learned interaction, a learned interaction corresponding to the probable physical action can be provided to the user.