Chargrid: Towards Understanding 2D Documents
Anoop R Katti | Christian Reisswig | Cordula Guder | Sebastian Brarda | Steffen Bickel | Johannes Höhne | Jean Baptiste Faddoul
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
We introduce a novel type of text representation that preserves the 2D layout of a document. This is achieved by encoding each document page as a two-dimensional grid of characters. Based on this representation, we present a generic document understanding pipeline for structured documents. This pipeline makes use of a fully convolutional encoder-decoder network that predicts a segmentation mask and bounding boxes. We demonstrate its capabilities on an information extraction task from invoices and show that it significantly outperforms approaches based on sequential text or document images.
Interactive Relation Extraction in Main Memory Database Systems
Rudolf Schneider | Cordula Guder | Torsten Kilias | Alexander Löser | Jens Graupmann | Oleksandr Kozachuk
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations
We present INDREX-MM, a main memory database system for interactively executing two interwoven tasks, declarative relation extraction from text and their exploitation with SQL. INDREX-MM simplifies these tasks for the user with powerful SQL extensions for gathering statistical semantics, for executing open information extraction and for integrating relation candidates with domain specific data. We demonstrate these functions on 800k documents from Reuters RCV1 with more than a billion linguistic annotations and report execution times in the order of seconds.
- Anoop R Katti 1
- Christian Reisswig 1
- Sebastian Brarda 1
- Steffen Bickel 1
- Johannes Höhne 1
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