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Text-analysis agent generating formal model from task description

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F22%3A00365417" target="_blank" >RIV/68407700:21730/22:00365417 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.ciirc.cvut.cz/cs/research-education/projects/nck-kui/sub03/v10/" target="_blank" >https://www.ciirc.cvut.cz/cs/research-education/projects/nck-kui/sub03/v10/</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Text-analysis agent generating formal model from task description

  • Original language description

    The outcome of this research is a Natural Language Processing (NLP) algorithm designed to analyze text, particularly users' manuals. The primary objective of the algorithm is to extract step-by-step procedures for setting up, maintaining, and troubleshooting specific devices from the manuals.

  • Czech name

  • Czech description

Classification

  • Type

    R - Software

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/TN01000024" target="_blank" >TN01000024: National Competence Center - Cybernetics and Artificial Intelligence</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2022

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Internal product ID

    TN01000024/3 - V10

  • Technical parameters

    To achieve this, we employed advanced information retrieval algorithms based on the representation of text chunks. Several different techniques based on embeddings were used to represent these text chunks. To evaluate the Semantic Text Similarity task, we utilized cosine similarity.

  • Economical parameters

    The resulting algorithm is a powerful tool that can effectively analyze and extract information from complex manuals, making it easier for users to understand and follow the step-by-step procedures.

  • Owner IČO

    68407700

  • Owner name

    České vysoké učení technické v Praze, CIIRC