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Authors: Daniel Schuster ; Daniel Esser ; Klemens Muthmann and Alexander Schill

Affiliation: Technische Universität Dresden, Germany

Keyword(s): Self-learning Information Extraction, Cooperative Extraction, Document Archiving, Business Documents.

Related Ontology Subjects/Areas/Topics: Collaborative Computing ; Coupling and Integrating Heterogeneous Data Sources ; Databases and Information Systems Integration ; Distributed Database Systems ; Enterprise Information Systems ; Software Agents and Internet Computing

Abstract: Business document indexing for ordered filing of documents is a crucial task for every company. Since this is a tedious error prone work, automatic or at least semi-automatic approaches have a high value. One approach for semi-automated indexing of business documents uses self-learning information extraction methods based on user feedback. While these methods require no management of complex indexing rules, learning by user feedback requires each user to first provide a number of correct extractions before getting appropriate automatic results. To eliminate this cold start problem we propose a cooperative approach to document information extraction involving dynamic hierarchies of extraction services. We provide strategies for making the decision when to contact another information extraction service within the hierarchy, methods to combine results from different sources, as well as aging and split strategies to reduce the size of cooperatively used indexes. An evaluation with a larg e number of real-world business documents shows the benefits of our approach. (More)

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Paper citation in several formats:
Schuster, D.; Esser, D.; Muthmann, K. and Schill, A. (2015). Modelspace - Cooperative Document Information Extraction in Flexible Hierarchies. In Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 2: ICEIS; ISBN 978-989-758-096-3; ISSN 2184-4992, SciTePress, pages 321-329. DOI: 10.5220/0005376403210329

@conference{iceis15,
author={Daniel Schuster. and Daniel Esser. and Klemens Muthmann. and Alexander Schill.},
title={Modelspace - Cooperative Document Information Extraction in Flexible Hierarchies},
booktitle={Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 2: ICEIS},
year={2015},
pages={321-329},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005376403210329},
isbn={978-989-758-096-3},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 2: ICEIS
TI - Modelspace - Cooperative Document Information Extraction in Flexible Hierarchies
SN - 978-989-758-096-3
IS - 2184-4992
AU - Schuster, D.
AU - Esser, D.
AU - Muthmann, K.
AU - Schill, A.
PY - 2015
SP - 321
EP - 329
DO - 10.5220/0005376403210329
PB - SciTePress

- Science and Technology Publications, Lda.
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