International Business Machines Corporation

Sarika Budhiraja

Lisa Seacat DeLuca

Schuyler Bruce Matthews

Jonathan D Dunne

Alessandro Donatelli

Bhavna Agrawal

Anuradha Bhamidipaty

Manus Kevin McHugh

Jonathan Tristan O'Gorman

Kyle Harding

Kevin Buonagurio

Brian Russell Garrett

Jayshree Sanjayam

A computer-implemented method can determine a linguistic boundary condition for synthetic data generation in a multi-class classification problem. The method includes analyzing empirical labelled data using linguistic and vector representation techniques. The method further includes deriving a synthetic boundary conditional (SBC) model based on the analysis of the empirical labelled data and identifying a boundary location for performant synthetic data generation using the SBC model.

Boundary detection for synthetic data generation

The exemplary embodiments disclose a method, a computer program product, and a computer system for obtaining a digital twin asset. The exemplary embodiments may include collecting input data, extracting one or more features from the input data, searching for a digital twin asset based on the extracted one or more features and one or more models, and facilitating an exchange of the digital twin asset.

Digital twin asset search

A method, computer system, and a computer program product for deep tagging a recorded review session is provided. The present invention may include identifying a recording segment referencing an artifact in a recorded review session. The present invention may also include generating a bi-directional link between the identified recording segment and the referenced artifact.

Deep tagging artifact review session

One or more computer processors associate a source code repository with a video session, wherein the source code repository contains one or more source code issues. The one or more computer processors identify one or more source code issues within the video session. The one or more computer processors create a plurality of video session segments based on the one or more identified source code issues within the video session and the associated source code repository. The one or more computer processors tag the created plurality of video session segments with corresponding source code issue information.

Deep tagged source code issue management

A method of expert peer identification includes receiving, from a user, a request for an expert peer for an asset type, and obtaining asset interaction data relevant to the request including a list of assets, and, for each asset on the list, values for each of a set of pre-defined interaction categories for each worker that has interacted with the asset. The method further includes, for each asset on the list, respectively multiplying the interaction category values by a corresponding set of category weights to obtain a set of weighted interaction values, and, for each worker, processing the sum of their weighted interaction values to obtain an overall centrality measure. The method also includes selecting one of the workers as the expert peer based, at least in part, on their overall centrality measure, and identifying the expert peer to the user.

Asset management expert peer identification

A method for inventory management performed by a computerized inventory management system includes, with an inventory management system, receiving an initial inventory line comprising an item, a quantity, and a bin. The method further includes, with the inventory management system providing a split quantity user interface window in response to determining that the quantity of the item exceeds an actual quantity stored at the bin, creating and displaying a plurality of new inventory lines to replace the first inventory line in response to an autosplit control of the user interface being engaged, the new inventory lines including different bins, and providing a control through the user interface window to allow manual adjustment of the new inventory lines.

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Westford, MA, United States of America

Sarika Budhiraja