AI Assistant for Process Plant Operations
AI-based Decision Assistant for Process Plant Operations (ADAPPO or Plant Assistant in short) is an applied research project conducted as a collaboration between GippLab and eschbach GmbH funded by ZIM (Zentrales Innovationsprogramm Mittelstand) run by the German Ministry of Economic Affairs and Climate Action. The collaboration has already been recognized with multiple industry awards.
NLP-driven Plant Assistant aims to create a tool that supports plant operators in their daily operations in an industrial processing plant. The Plant Assistant aggregates knowledge and experience from logged plant operations and provides fast, efficient, and interactive feedback when users need solutions to encountered problems. A goal of the project is to leverage the recent advances in NLP to tailor language models towards domain-specific text data of multiple languages with uneven data quality, data scarcity, and lack of annotated sources.
Plant Assistant involves the following NLP research and tasks:
- Domain adaptation of language models
- Document encoders
- Information extraction & linking
- Text classification
- Text summarization
- Retrieval-augmented generation
- Chat-bot
Check out our ongoing projects that are available as B.Sc./M.Sc. theses here.
Related Publications
- ANEA: Automated (Named) Entity Annotation for German Domain-Specific Texts
A. Zhukova, F. Hamborg, and B. Gipp
in Proceedings of the 2nd Workshop on Extraction and Evaluation of Knowledge Entities from Scientific Documents (EEKE 2021) co-located with JCDL 2021, Virtual Event, Illinois, USA, 2021.
PDF - Generative User-Experience Research for Developing Domain-specific Natural Language Processing Applications
A. Zhukova, L. von Sperl, C. E. Matt, and B. Gipp
Knowledge and Information Systems, DOI 10.1007/s10115-024-02212-5, 2024
PDF
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