Deep Learning based Key Information Extraction from Business Documents: Systematic Literature Review

TL;DR

This paper systematically reviews deep learning methods for extracting key information from business documents, analyzing 130 approaches from 2017 to 2024 to identify current trends and future research opportunities.

Contribution

It provides a comprehensive analysis of recent deep learning approaches for key information extraction in business documents, highlighting research gaps and future directions.

Findings

Deep learning methods have significantly advanced document understanding.

Most approaches focus on invoice and receipt processing.

There is a need for standardized benchmarks and datasets.

Abstract

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, 130 approaches published between 2017 and 2024 are analyzed in this study.