Information Extraction from Invoices: A Graph Neural Network Approach for Datasets with High Layout Variety

[1]  Ole Winther,et al.  CloudScan - A Configuration-Free Invoice Analysis System Using Recurrent Neural Networks , 2017, 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR).

[2]  Steffen Bickel,et al.  Chargrid: Towards Understanding 2D Documents , 2018, EMNLP.

[3]  Michael A. Osborne,et al.  The future of employment: How susceptible are jobs to computerisation? , 2017 .

[4]  Ameet Talwalkar,et al.  Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization , 2016, J. Mach. Learn. Res..

[5]  Yolande Belaïd,et al.  An Invoice Reading System Using a Graph Convolutional Network , 2018, ACCV Workshops.

[6]  Bertin Klein,et al.  smartFIX: A Requirements-Driven System for Document Analysis and Understanding , 2002, Document Analysis Systems.

[7]  Xiaojing Liu,et al.  Graph Convolution for Multimodal Information Extraction from Visually Rich Documents , 2019, NAACL.

[8]  Alexander Schill,et al.  Intellix -- End-User Trained Information Extraction for Document Archiving , 2013, 2013 12th International Conference on Document Analysis and Recognition.

[9]  Christian Reisswig,et al.  BERTgrid: Contextualized Embedding for 2D Document Representation and Understanding , 2019, ArXiv.

[10]  Daniel P. Lopresti,et al.  Document Analysis Systems V , 2002, Lecture Notes in Computer Science.

[11]  Alexander Schill,et al.  Automatic indexing of scanned documents: a layout-based approach , 2012, Electronic Imaging.

[12]  Ming-Wei Chang,et al.  BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding , 2019, NAACL.

[13]  Sandeep Tata,et al.  Representation Learning for Information Extraction from Form-like Documents , 2020, ACL.

[14]  Yoshua Bengio,et al.  Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation , 2014, EMNLP.