Abstract: According to one embodiment, a method, computer system, and computer program product for mixed-reality peripheral interfacing is provided. The present invention may include recording, with a camera, video footage of a peripheral held by a user participating in a mixed-reality environment; extracting, by a processor, peripheral data from the video footage; extracting interface data from the video footage; extracting input data entered into the peripheral by the user; responsive to determining that one or more keybindings do not match the peripheral, rebinding one or more keybindings of the peripheral based on the peripheral data; displaying a virtual representation of the peripheral to the user within the mixed-reality environment based on the peripheral data; and displaying a virtual representation of the user interacting with the virtual representation of the peripheral within the mixed-reality environment based on the interface data and the input data.

Abstract: Provided are a method, system, and computer program product for representing text, in which a text is received and analyzed by utilizing a pre-trained embedding model and a feature vector model, wherein selected words in the text have corresponding weights. Operations whose parameters include weights of a feature vector and an embedding are performed to generate a weighted embedding data structure. A summation is performed of all corresponding columns of a plurality of rows of the weighted embedding data structure to generate a data structure that represents the text. The data structure that represents the text is utilized to generate at least one of a classification metadata for the text and a summarization of the text.

Abstract: Provided are a method, system, and computer program product for representing text, in which a text is received and analyzed by utilizing a pre-trained embedding model and a feature vector model, wherein selected words in the text have corresponding weights. Operations whose parameters include weights of a feature vector and an embedding are performed to generate a weighted embedding data structure. A summation is performed of all corresponding columns of a plurality of rows of the weighted embedding data structure to generate a data structure that represents the text. The data structure that represents the text is utilized to generate at least one of a classification metadata for the text and a summarization of the text.