Concept relation discovery and innovation enabling technology (CORDIET)

Open Access
Authors
  • J. Poelmans
  • P. Elzinga
  • A. Neznanov
  • S. Viaene
  • S.O. Kuznetsov
  • D. Ignatov
  • G. Dedene
Publication date 2011
Host editors
  • D.I. Ignatov
  • S.O. Kuznetsov
  • J. Poelmans
Book title Proceedings of the International Workshop on Concept Discovery in Unstructured Data (CDUD 2011)
Book subtitle in conjunction with the Thirteenth International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing - RSFDGrC 2011 : Moscow, Russia, June 25, 2011
Series CEUR Workshop Proceedings
Event Concept Discovery in Unstructured Data (CDUD 2011)
Pages (from-to) 53-62
Publisher Aachen: CEUR-WS
Organisations
  • Faculty of Economics and Business (FEB) - Amsterdam Business School Research Institute (ABS-RI)
Abstract
Concept Relation Discovery and Innovation Enabling Technology (CORDIET), is a toolbox for gaining new knowledge from unstructured text data. At the core of CORDIET is the C-K theory which
captures the essential elements of innovation. The tool uses Formal Concept Analysis (FCA), Emergent Self Organizing Maps (ESOM) and Hidden Markov Models (HMM) as main artifacts in the analysis process. The user can define temporal, text mining and compound attributes. The text mining attributes are used to analyze the unstructured text in documents, the temporal attributes use these document’s timestamps for analysis. The compound attributes are XML rules based on text mining and temporal attributes. The user can cluster objects with object-cluster rules and can
chop the data in pieces with segmentation rules. The artifacts are optimized for efficient data analysis; object labels in the FCA lattice and ESOM map contain an URL on which the user can click to open the selected document.
Document type Conference contribution
Language English
Published at http://ceur-ws.org/Vol-757/paper_6.pdf
Other links http://ceur-ws.org/Vol-757/
Downloads
CORDIET.pdf (Final published version)
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