Kyndryl, Inc.

International Business Machines Corporation

Pedro Soares

Clea Anne Zolotow

John F Graham

Saritha Route

Simon J Brady

Barry Hollywood

Jørgen Egbert Floes

Ana Maria Bezerra Maimoni

Thomas Brackhahn

Hasibe Göçülü

Anastasios Xouzafeiris

In an approach for a smart reading assistant that helps users learn to read a new language, a processor detects a language of a digital book opening by a user on a computing device. A processor identifies a user reading capability level for the language of the digital book from a user profile for the user. A processor inputs at least one in context meaning of potential unknown words based on the user reading capability level. A processor detects a user action by the user on the computing device. A processor updates the user reading capability level based on the user action. A processor identifies, using collocation extraction, related words to a word involved in the user action. A processor inputs at least one in context meaning of at least one of the related words.

Smart reading assistant

A method for retrieving a plurality of electronic images that includes obtaining images from a plurality of electronic storage sites. A first set of images containing a main protagonist is selected from the plurality of electronic images. An intent based image selection is performed from the first set of images. The intent based image selection includes tagging the first set of images with word tags identifying content of the images, creating a word cloud from the word tags, plotting the top word tags from the word cloud in a Venn diagram, and extracting images from the overlapping are of the Venn diagram.

Artificial intelligence driven image retrieval

A computer system manages multi-stage transactions. A plurality of response time values of transaction components for a plurality of transactions are received. Two or more transactions from the plurality of transactions are selected, wherein a quantity of the selected transactions is equal to a number of the transaction components in the plurality of transactions. Eigenvalues are calculated from the response time values for the selected transactions. The selected transactions are determined to have timed out by processing the eigenvalues using a machine learning classifier. Embodiments of the present invention further include a method and program product for managing multi-stage transactions in substantially the same manner described above.

Watchdog timer for a multi-stage computing environment

Growing community of inventors

Silveira, Portugal

Pedro Soares