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 analysis concept fca formal information ir retrieval
%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 = {2012-02-23T14:50:59.000+0100},
author = {Poelmans, Jonas and Elzinga, Paul and Viaene, Stijn and Dedene, Guido and Kuznetsov, Sergei O.},
biburl = {https://www.bibsonomy.org/bibtex/2164c37be60c1a47d1727ad9b82f01237/jaeschke},
booktitle = {Industrial Conference on Data Mining - Poster and Industry Proceedings},
editor = {Perner, Petra},
interhash = {b44d11ea5b5a4df8ee30a9c572d82051},
intrahash = {164c37be60c1a47d1727ad9b82f01237},
isbn = {978-3-942954-06-4},
keywords = {analysis concept fca formal information ir retrieval},
pages = {82--96},
publisher = {IBaI Publishing},
timestamp = {2014-07-28T15:57:31.000+0200},
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
}