Deep Learning based Key Information Extraction from Business Documents: Systematic Literature Review
Extracting key information from documents represents a large portion of business workloads and therefore offers a high potential for efficiency improvements and process automation. With recent advances in deep learning, a plethora of deep learning-based approaches for Key Information Extraction have been proposed under the umbrella term Document Understanding that enable the processing of complex business documents. The goal of this systematic literature review is an in-depth analysis of existing approaches in this domain and the identification of opportunities for further research. To this end, 96 approaches published between 2017 and 2023 are analyzed in this study.
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Deep Learningdocument understandingKey Information ExtractionSystematic Literature ReviewSimilar Papers 제목 키워드 기반
Improving Information Extraction on Business Documents with Specific Pre-Training Tasks
Transformer-based Language Models are widely used in Natural Language Processing related tasks. Thanks to their pre-training, they have been successfully adapted to Information Extraction in business documents. However, …
Language ModelingLanguage ModellingJointly Learning Span Extraction and Sequence Labeling for Information Extraction from Business Documents
This paper introduces a new information extraction model for business documents. Different from prior studies which only base on span extraction or sequence labeling, the model takes into account advantage of both span e…
Business Document Information Extraction: Towards Practical Benchmarks
Information extraction from semi-structured documents is crucial for frictionless business-to-business (B2B) communication. While machine learning problems related to Document Information Extraction (IE) have been studie…
Rapid Adaptation of BERT for Information Extraction on Domain-Specific Business Documents
Techniques for automatically extracting important content elements from business documents such as contracts, statements, and filings have the potential to make business operations more efficient. This problem can be for…
BuDDIE: A Business Document Dataset for Multi-task Information Extraction
The field of visually rich document understanding (VRDU) aims to solve a multitude of well-researched NLP tasks in a multi-modal domain. Several datasets exist for research on specific tasks of VRDU such as document clas…
Document Classificationdocument understandingEntity LinkingLanguage Modelling+4