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Tools for Automatic Recognition of Persons and their Relationships in Unstructured Data
[Nástroje pro automatické rozpoznávání entit a jejich vztahů v nestrukturovaných textech]

Author

Listed:
  • Jaroslav Ráček
  • Jan Ministr

Abstract

The article deals with the specifics of the three layer architecture of software for automatic detection and identification of persons, objects and relationships in unstructured data. The data layer consists of data acquisition and data management modules. The application layer is composed of separate modules that can be combined to meet the needs of specific investigative tasks. The presentation layer makes the analysis of results for police investigation. The overall solution is demonstrated on develop the system ARIO which is applicable for a range of national and international institutions as well as private entities.

Suggested Citation

  • Jaroslav Ráček & Jan Ministr, 2014. "Tools for Automatic Recognition of Persons and their Relationships in Unstructured Data [Nástroje pro automatické rozpoznávání entit a jejich vztahů v nestrukturovaných textech]," Acta Informatica Pragensia, Prague University of Economics and Business, vol. 2014(3), pages 280-287.
    • Handle: RePEc:prg:jnlaip:v:2014:y:2014:i:3:id:54:p:280-287
    DOI: 10.18267/j.aip.54
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    References listed on IDEAS

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    1. Triss Ashton & Nicholas Evangelopoulos & Victor Prybutok, 2014. "Extending monitoring methods to textual data: a research agenda," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(4), pages 2277-2294, July.
    2. Moshe Koppel & Jonathan Schler & Shlomo Argamon, 2009. "Computational methods in authorship attribution," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(1), pages 9-26, January.
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