Paper Info
Title
Concept Relation Discovery and Innovation Enabling Technology (CORDIET)
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.
Year
DOI
Venue
2012
10.2139/ssrn.1713124
CoRR
Keywords
Field
DocType
hidden markov model,formal concept analysis,rule based,text mining,data analysis
Data mining,Text mining,Information retrieval,XML,Segmentation,Computer science,Toolbox,Self-organizing map,Timestamp,Hidden Markov model,Formal concept analysis
Journal
Volume
ISSN
Citations 
abs/1202.2895
In CEUR Workshop proceedings Vol-757, CDUD'11 - Concept Discovery in Unstructured Data, pp. 53-62, 2011
4
PageRank 
References 
Authors
0.55
15
7
Name
Order
Citations
PageRank
Jonas Poelmans127719.28
Paul Elzinga21229.14
Alexey Neznanov3185.10
Stijn Viaene472260.17
Sergei O. Kuznetsov51630121.46
Dmitry I. Ignatov623929.53
Guido Dedene792583.39