Formal Concept Analysis (FCA) is an unsupervised
clustering technique and many scientific papers are
devoted to applying FCA in Information Retrieval (IR)
research. We collected 103 papers published between
2003-2009 which mention FCA and information retrieval
in the abstract, title or keywords. Using a prototype
of our FCA-based toolset CORDIET, we converted the
pdf-files containing the papers to plain text,
indexed them with Lucene using a thesaurus containing
terms related to FCA research and then created the
concept lattice shown in this paper. We visualized,
analyzed and explored the literature with concept
lattices and discovered multiple interesting research
streams in IR of which we give an extensive overview.
The core contributions of this paper are the
innovative application of FCA to the text mining of
scientific papers and the survey of the FCA-based IR
research.
%0 Conference Paper
%1 poelmans2011mining
%A Poelmans, Jonas
%A Elzinga, Paul
%A Viaene, Stijn
%A Dedene, Guido
%A Kuznetsov, Sergei O.
%B Industrial Conference on Data Mining - Poster and
Industry Proceedings
%D 2011
%E Perner, Petra
%I IBaI Publishing
%K 2012 citedBy:doerfel2012publication icfca mining scientometry text
%P 82--96
%T Text Mining Scientific Papers: a Survey on
FCA-based Information Retrieval Research.
%U http://dblp.uni-trier.de/db/conf/incdm/ incdm2011p.html#PoelmansEVDK11
%X Formal Concept Analysis (FCA) is an unsupervised
clustering technique and many scientific papers are
devoted to applying FCA in Information Retrieval (IR)
research. We collected 103 papers published between
2003-2009 which mention FCA and information retrieval
in the abstract, title or keywords. Using a prototype
of our FCA-based toolset CORDIET, we converted the
pdf-files containing the papers to plain text,
indexed them with Lucene using a thesaurus containing
terms related to FCA research and then created the
concept lattice shown in this paper. We visualized,
analyzed and explored the literature with concept
lattices and discovered multiple interesting research
streams in IR of which we give an extensive overview.
The core contributions of this paper are the
innovative application of FCA to the text mining of
scientific papers and the survey of the FCA-based IR
research.
%@ 978-3-942954-06-4
@inproceedings{poelmans2011mining,
abstract = {Formal Concept Analysis (FCA) is an unsupervised
clustering technique and many scientific papers are
devoted to applying FCA in Information Retrieval (IR)
research. We collected 103 papers published between
2003-2009 which mention FCA and information retrieval
in the abstract, title or keywords. Using a prototype
of our FCA-based toolset CORDIET, we converted the
pdf-files containing the papers to plain text,
indexed them with Lucene using a thesaurus containing
terms related to FCA research and then created the
concept lattice shown in this paper. We visualized,
analyzed and explored the literature with concept
lattices and discovered multiple interesting research
streams in IR of which we give an extensive overview.
The core contributions of this paper are the
innovative application of FCA to the text mining of
scientific papers and the survey of the FCA-based IR
research.},
added-at = {2012-03-05T11:20:40.000+0100},
author = {Poelmans, Jonas and Elzinga, Paul and Viaene, Stijn and Dedene, Guido and Kuznetsov, Sergei O.},
biburl = {https://www.bibsonomy.org/bibtex/2164c37be60c1a47d1727ad9b82f01237/kde},
booktitle = {Industrial Conference on Data Mining - Poster and
Industry Proceedings},
editor = {Perner, Petra},
interhash = {b44d11ea5b5a4df8ee30a9c572d82051},
intrahash = {164c37be60c1a47d1727ad9b82f01237},
isbn = {978-3-942954-06-4},
keywords = {2012 citedBy:doerfel2012publication icfca mining scientometry text},
pages = {82--96},
publisher = {IBaI Publishing},
timestamp = {2012-03-05T11:25:04.000+0100},
title = {Text Mining Scientific Papers: a Survey on
{FCA}-based Information Retrieval Research.},
url = {http://dblp.uni-trier.de/db/conf/incdm/ incdm2011p.html#PoelmansEVDK11},
year = 2011
}