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Natural Language Processing in IT Ticketing Systems. A conceptual framework for Question-and-Answering machines based on GPT-Algorithms

Author

Listed:
  • Becker, Marcus
  • Prokop Dayrell de Lima, Erika

Abstract

This research is a feasibility study to design a Natural Language Processing (NLP) system within a Ques-tion-and-Answering (Q&A) environment for internal IT help desk ticketing operations. The proceedings will be used to develop a conversational agent for an IT consultancy company. Tests with few-shot learning algorithms were performed by calibrating two GPT-2 language models. Another benchmark model was tested on the most recent GPT-3 standard. The input data stems from software license release requests of an internal IT help desk. The final model will be a hybrid approach of first guidance by an automated agent and a human expert intervention for more complicated IT problem. The agent will improve itself by constantly evaluating user feedback.

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Handle: RePEc:zbw:ismrja:324733
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JEL classification:

  • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
  • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
  • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management
  • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
  • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

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