Information Extraction from Financial Tables: Application and Evaluation of a Machine Learning Approach in Annual Reports
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Authors
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Publication date
2025
Type of student thesis
Master
Course of study
Collections
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11 - Student thesis
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Hochschule für Wirtschaft FHNW
Place of publication / Event location
Olten
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Abstract
In recent years, specialized deep-learning models have demonstrated promising results in extracting table information from PDFs. In addition, multi-module solutions have been developed to process complex PDF documents and optimally align the extraction techniques to the different document components. Furthermore, Large Language Models (LLMs) have shown a comprehensive language understanding. However, the performance of these new possibilities has not yet been validated in an end-to-end process on a dataset of annual reports.
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English
Created during FHNW affiliation
Yes
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Review
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Citation
Dimmler, H.-R. (2025). Information Extraction from Financial Tables: Application and Evaluation of a Machine Learning Approach in Annual Reports [Hochschule für Wirtschaft FHNW]. https://irf.fhnw.ch/handle/11654/54840