Abstract: A method and system for improving memory reorganization and storage technology is provided. The method includes configuring data capture settings of a database system resulting in configured data capture settings. Data objects associated with a user are retrieved and stored in a database. Overlapping data elements of the data objects are determined and associated collaboration data model software code is generated. A request for first data is received and mapped to the data objects. A clone data object associated with the first data object is generated with respect to the overlapping data elements.

Abstract: Disclosed embodiments provide techniques for estimating the accuracy of a user rating score. In embodiments, a user rating score is obtained from a user. Online activity events such as social media posts, purchases, cancellations, online reviews, and/or other activities are analyzed by a computer system to determine a level of agreement between the score the user provided, and the online activity events of the user that pertain to the product and/or service to which the score pertains. A user rating score reliability factor is computed based on the level of agreement and can be made available to stakeholders such as product managers, marketing personnel, and sales teams.

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.

Abstract: A ticket relating to a software event is received in a software development system. One or more public forums on software development is searched for the software event. Two or more topics on the software event are identified from one or more conversations from the one or more public forums that regard the software event. Two or more causes of the software event are determined by analyzing interrelations of the two or more topics.

Abstract: Self-executing document revision includes creating a current version of an electronic rendering of a collaborative document based on input received from a user via a communicative coupling with a data communications network. The current version's relevancy is determined by a self-executing document revisor and compared with the relevancy of a prior version of the collaborative document. In response to determining the relevancy of the current version is less than the relevancy of the prior version, one or more segments of one or more electronically stored versions of the collaborative document are selected based on a relevancy of each of the one or more segments, the relevancy of each determined by the self-executing document revisor. The self-executing document revisor generates a graphical representation of a revised version of the collaborative document by merging the one or more segments selected with the current version of the collaborative document.

Abstract: Disentanglement of chat utterances is provided. An analysis of the linguistic collocations and the keywords of the multiple chat utterances and amount of contribution by respective chat users of the plurality of chat users to the multiple chat utterances is performed to determine a level of drift of the linguistic collocations, the keywords, and respective chat users over a course of the multiple chat utterances. Chat utterance entanglement of prior chat utterances is determined using determined level of drift based on the analysis by inferring keyword usage over time and how these keywords are related over the course of the multiple chat utterances. The prior chat utterances related to a particular topic are disentangled by removing certain chat utterances that have a statistically significant level of drift from that particular topic. Removed chat utterances are arranged as a new chat discourse related to a different topic in the chat conversation.

Abstract: A method, computer system, and computer program product for dynamic meeting agenda management are provided. The embodiment may include establishing a baseline set of agenda items prior to meeting commencement. The embodiment may also include identifying meeting participants based on actual real-time meeting attendance. The embodiment may further include monitoring an attendance and a participation of the meeting participants. The embodiment may also include identifying the agenda items that meet selection criteria using a coverage triggering mechanism. The embodiment may further include updating the order of the agenda items based on the agenda item that meet selection criteria first. The embodiment may also include displaying real-time meeting agenda items that meet the selection criteria.

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: A method of filtering images of live stream content may include defining a prohibited frame content template; analyzing live stream content at a frame level to determine content within each frame of the live stream content; and comparing a frame of the live stream content against the prohibited frame content template to detect prohibited content in the frame that matches prohibited frame content as defined by the prohibited frame content template.

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: An embodiment of a summarization application divides collected conversation data into media and text components. The application implements respective machine learning mechanisms to enhance modeling operations of the text and media components to identify key elements from the conversation. The application generates a headline banner from a group of key elements based on an analysis involving first predetermined criteria. The application also combines additional key elements to the group of key elements to form a second group of key elements. The application generates a summary from the second group of key elements based on a second analysis involving second predetermined criteria. The application presents, via a display, the headline banner according to a first output of the first key element analysis and the summary according to a second output of the second key element analysis.

Abstract: Self-executing document revision includes creating a current version of an electronic rendering of a collaborative document based on input received from a user via a communicative coupling with a data communications network. The current version's relevancy is determined by a self-executing document revisor and compared with the relevancy of a prior version of the collaborative document. In response to determining the relevancy of the current version is less than the relevancy of the prior version, one or more segments of one or more electronically stored versions of the collaborative document are selected based on a relevancy of each of the one or more segments, the relevancy of each determined by the self-executing document revisor. The self-executing document revisor generates a graphical representation of a revised version of the collaborative document by merging the one or more segments selected with the current version of the collaborative document.

Abstract: A method, system and computer program product for automatically distributing tasks within a group includes identifying, by one or more processors, first data associated with each member of a group. The one or more processors identify second data associated with demands for the group, calculate a total work time for each member of the group using the first data, identify conflicts between the total work time for each member of the group and the second data, and based on the identified conflict, distribute tasks among members of the group.

Abstract: Disentanglement of chat utterances is provided. An analysis of the linguistic collocations and the keywords of the multiple chat utterances and amount of contribution by respective chat users of the plurality of chat users to the multiple chat utterances is performed to determine a level of drift of the linguistic collocations, the keywords, and respective chat users over a course of the multiple chat utterances. Chat utterance entanglement of prior chat utterances is determined using determined level of drift based on the analysis by inferring keyword usage over time and how these keywords are related over the course of the multiple chat utterances. The prior chat utterances related to a particular topic are disentangled by removing certain chat utterances that have a statistically significant level of drift from that particular topic. Removed chat utterances are arranged as a new chat discourse related to a different topic in the chat conversation.

Abstract: A computer system performs an action on an object identified from a command. A command is analyzed to perform an action on a target object, wherein the command includes a term for the target object that refers to a plurality of different candidate objects. The target object is identified from the plurality of different candidate objects based on historical associations of the term with specific ones of the candidate objects, recent interactions with the different candidate objects, and a state of the candidate objects provided by network devices. The action is performed on the identified target object. Embodiments of the present invention further include a method and program product for performing an action on an object identified from a command in substantially the same manner described above.

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 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: 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: An embodiment of a summarization application divides collected conversation data into media and text components. The application implements respective machine learning mechanisms to enhance modeling operations of the text and media components to identify key elements from the conversation. The application generates a headline banner from a group of key elements based on an analysis involving first predetermined criteria. The application also combines additional key elements to the group of key elements to form a second group of key elements. The application generates a summary from the second group of key elements based on a second analysis involving second predetermined criteria. The application presents, via a display, the headline banner according to a first output of the first key element analysis and the summary according to a second output of the second key element analysis.

Abstract: A method, computer system, and a computer program product for voice assistant responses is provided. The present invention may include configuring a behavioral rule. The present invention may include receiving a verbal request from a user and comparing the received verbal request to the behavioral rule. The present invention may then include determining that the received verbal request does not comply with the behavioral rule. The present invention may lastly include providing a response to the user based on determining that the received verbal request does not comply with the behavioral rule.