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User experience (UX) is a part of human-computer interaction (HCI) researchand focuses on increasing intuitiveness, transparency, simplicity, and trustfor the system users. Most UX research for machine learning (ML) or naturallanguage processing (NLP) focuses on a data-driven methodology. It engagesdomain users mainly for usability evaluation. Moreover, more typical UX methodstailor the systems towards user usability, unlike learning about the user needsfirst. This paper proposes a new methodology for integrating generative UXresearch into developing domain NLP applications. Generative UX researchemploys domain users at the initial stages of prototype development, i.e.,ideation and concept evaluation, and the last stage for evaluating systemusefulness and user utility. The methodology emerged from and is evaluated on acase study about the full-cycle prototype development of a domain-specificsemantic search for daily operations in the process industry. A key finding ofour case study is that involving domain experts increases their interest andtrust in the final NLP application. The combined UX+NLP research of theproposed method efficiently considers data- and user-driven opportunities andconstraints, which can be crucial for developing NLP applications.

Generative User-Experience Research for Developing Domain-specific Natural Language Processing Applications