TY - CHAP AU - Poelmans, Jonas AU - Ignatov, DmitryI. AU - Viaene, Stijn AU - Dedene, Guido AU - Kuznetsov, SergeiO. A2 - Perner, Petra T1 - Text Mining Scientific Papers: A Survey on FCA-Based Information Retrieval Research T2 - Advances in Data Mining. Applications and Theoretical Aspects PB - Springer Berlin Heidelberg C1 - PY - 2012/ VL - 7377 IS - SP - 273 EP - 287 UR - http://dx.doi.org/10.1007/978-3-642-31488-9_22 DO - 10.1007/978-3-642-31488-9_22 KW - FCA KW - IR KW - Mining KW - SOTA KW - Text L1 - SN - 978-3-642-31487-2 N1 - Text Mining Scientific Papers: A Survey on FCA-Based Information Retrieval Research - Springer N1 - AB - 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. ER - TY - CONF AU - Doerfel, Stephan AU - Jäschke, Robert AU - Stumme, Gerd A2 - Domenach, F. A2 - Ignatov, D.I. A2 - Poelmans, J. T1 - Publication Analysis of the Formal Concept Analysis Community T2 - ICFCA 2012 PB - Springer C1 - Berlin/Heidelberg PY - 2012/ CY - VL - 7278 IS - SP - 77 EP - 95 UR - https://www.kde.cs.uni-kassel.de/pub/pdf/doerfel2012publication.pdf DO - KW - 2012 KW - analysis KW - community KW - concept KW - fca KW - home KW - info20pub KW - itegpub KW - l3s KW - myown KW - scientometrics L1 - SN - N1 - N1 - AB - We present an analysis of the publication and citation networks of all previous editions of the three conferences most relevant to the FCA community: ICFCA, ICCS and CLA. Using data mining methods from FCA and graph analysis, we investigate patterns and communities among authors, we identify and visualize influential publications and authors, and we give a statistical summary of the conferences’ history.

ER - TY - CHAP AU - Cimiano, Philipp AU - Hotho, Andreas AU - Stumme, Gerd AU - Tane, Julien A2 - Eklund, Peter T1 - Conceptual Knowledge Processing with Formal Concept

Analysis and Ontologies T2 - Concept Lattices PB - Springer C1 - Berlin/Heidelberg PY - 2004/ VL - 2961 IS - SP - 189 EP - 207 UR - http://dx.doi.org/10.1007/978-3-540-24651-0_18 DO - KW - 2004 KW - citedBy:doerfel2012publication KW - fca KW - icfca KW - itegpub KW - knowledge KW - l3s KW - myown KW - processing L1 - SN - 978-3-540-21043-6 N1 - N1 - AB - ER - TY - JOUR AU - Stumme, Gerd AU - Taouil, Rafik AU - Bastide, Yves AU - Pasquier, Nicolas AU - Lakhal, Lotfi T1 - Computing iceberg concept lattices with TITANIC JO - Data & Knowledge Engineering PY - 2002/ VL - 42 IS - 2 SP - 189 EP - 222 UR - http://portal.acm.org/citation.cfm?id=606457 DO - 10.1016/S0169-023X(02)00057-5 KW - citedBy:doerfel2012publication KW - fca KW - icfca KW - itegpub KW - l3s KW - myown KW - titanic L1 - SN - N1 - N1 - AB - We introduce the notion of iceberg concept lattices

and show their use in knowledge discovery in

databases. Iceberg lattices are a conceptual

clustering method, which is well suited for analyzing

very large databases. They also serve as a condensed

representation of frequent itemsets, as starting

point for computing bases of association rules, and

as a visualization method for association rules.

Iceberg concept lattices are based on the theory of

Formal Concept Analysis, a mathematical theory with

applications in data analysis, information retrieval,

and knowledge discovery. We present a new algorithm

called TITANIC for computing (iceberg) concept

lattices. It is based on data mining techniques with

a level-wise approach. In fact, TITANIC can be used

for a more general problem: Computing arbitrary

closure systems when the closure operator comes along

with a so-called weight function. The use of weight

functions for computing closure systems has not been

discussed in the literature up to now. Applications

providing such a weight function include association

rule mining, functional dependencies in databases,

conceptual clustering, and ontology engineering. The

algorithm is experimentally evaluated and compared

with Ganter's Next-Closure algorithm. The evaluation

shows an important gain in efficiency, especially for

weakly correlated data. ER - TY - CONF AU - Jäschke, Robert AU - Rudolph, Sebastian A2 - Cellier, Peggy A2 - Distel, Felix A2 - Ganter, Bernhard T1 - Attribute Exploration on the Web T2 - Contributions to the 11th International Conference on Formal Concept Analysis PB - C1 - PY - 2013/05 CY - VL - IS - SP - 19 EP - 34 UR - http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-113133 DO - KW - 2013 KW - acquisition KW - analysis KW - attribute KW - computing KW - concept KW - crowdsourcing KW - data KW - exploration KW - fca KW - formal KW - human KW - information KW - ir KW - iteg KW - knowledge KW - l3s KW - linked KW - lod KW - open KW - retrieval KW - search KW - sparql KW - web L1 - SN - N1 - N1 - AB - We propose an approach for supporting attribute exploration by web information retrieval, in particular by posing appropriate queries to search engines, crowd sourcing systems, and the linked open data cloud. We discuss underlying general assumptions for this to work and the degree to which these can be taken for granted. ER -