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Computer Networks

Finished Reference Project

Project:

Modelspace - Hierarchical Model Spaces for Cooperative Efficient Data Extraction from Business Documents

  • Information Extraction
  • Business Document Processing
  • Machine Learning

Overview:

Within the research project Modelspace, we want to develop a highly distributed solution for the cooperation of indexing services for automatic indexing of business documents. It builds upon the indexing service from the project Intellix and focuses on cooperative information extraction in flexible hierarchies. The goal is to reduce manual indexing of each user as well as to improve the user experience in the start phase where there is still a low number of documents uploaded by the user. The project covers the following topics: Granularity of model spaces for machine learning, cooperation of model spaces along multi-level hierarchies, split and merge of model spaces, monitoring and performance optimization of a compound of indexing servers as well as intuitive user interfaces for feedback, training and administration. The project is done in cooperation with DocuWare GmbH Munich and runs from July 2012 until June 2014.


Project promotion:

Bundesministerium für Bildung und Forschung
01IS12017B


Project leader:

Prof. Dr. rer. nat. habil. Dr. h. c. Alexander Schill


Project staff:

Dr.-Ing. Daniel Esser
Dipl.-Inf. Marcel Hanke
Dr.-Ing. Klemens Muthmann
Dr.-Ing. Daniel Schuster


Resources:


Recent publications:


Student Assignments:

    1. Florian Siegmund:
    Analyse und Vorhersage von Aktualisierungen in App Stores;
    Großer Beleg; 12.06.2014; Supervising tutor: Daniel Esser

    2. Steffen Jasper:
    Monitoring verteilter Dienste für Datenextraktion;
    Diploma thesis; 26.09.2013; Supervising tutor: Daniel Schuster

    3. Markus Marks:
    Informationsextraktion aus Dokumenten anhand weniger Lernbeispiele;
    Bachelor thesis; 23.09.2013; Supervising tutor: Daniel Esser

    4. Steffen Matthischke:
    Mobile Dokumentenerfassung mit dem iPad;
    Großer Beleg; 29.01.2013; Supervising tutor: Daniel Schuster


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