Bicluster enumeration using Formal Concept Analysis
Identifieur interne : 001249 ( Hal/Curation ); précédent : 001248; suivant : 001250Bicluster enumeration using Formal Concept Analysis
Auteurs : Victor Codocedo [France] ; Amedeo Napoli [France]Source :
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Abstract
In this work we introduce a novel technique to enumerate constant row/column value biclusters using formal concept analysis. To achieve this, a numerical data-table (standard input for biclustering al-gorithms) is modelled as a many-valued context where rows represent objects and columns represent attributes. Using equivalence relations de-fined for each single column, we are able to translate the bicluster mining problem in terms of the partition pattern structure framework. We show how biclustering can benefit from the FCA framework through its ro-bust theoretical description and efficient algorithms. Finally, we show how this technique is able to find high quality biclusters (in terms of the mean squared error) more efficiently than a state-of-the-art bicluster algorithm.
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To achieve this, a numerical data-table (standard input for biclustering al-gorithms) is modelled as a many-valued context where rows represent objects and columns represent attributes. Using equivalence relations de-fined for each single column, we are able to translate the bicluster mining problem in terms of the partition pattern structure framework. We show how biclustering can benefit from the FCA framework through its ro-bust theoretical description and efficient algorithms. Finally, we show how this technique is able to find high quality biclusters (in terms of the mean squared error) more efficiently than a state-of-the-art bicluster algorithm.</div></front></TEI><hal api="V3"><titleStmt><title xml:lang="en">Bicluster enumeration using Formal Concept Analysis</title><author role="aut"><persName><forename type="first">Victor</forename><surname>Codocedo</surname></persName><email>victor.codocedo@loria.fr</email><idno type="halauthor">1125631</idno><affiliation ref="#struct-205125"></affiliation></author><author role="aut"><persName><forename type="first">Amedeo</forename><surname>Napoli</surname></persName><email>Amedeo.Napoli@loria.fr</email><idno type="halauthor">61765</idno><affiliation ref="#struct-205125"></affiliation></author><editor role="depositor"><persName><forename>Victor</forename><surname>Codocedo</surname></persName><email>victor.codocedo@inria.fr</email></editor></titleStmt><editionStmt><edition n="v1" type="current"><date type="whenSubmitted">2014-12-16 14:09:07</date><date type="whenModified">2015-09-22 01:12:33</date><date type="whenReleased">2014-12-18 15:31:47</date><date type="whenProduced">2014-08-09</date><date type="whenEndEmbargoed">2014-12-16</date><ref type="file" target="https://hal.inria.fr/hal-01095884/document"><date notBefore="2014-12-16"></date></ref><ref type="file" subtype="author" n="1" target="https://hal.inria.fr/hal-01095884/file/cona-fca4ai14-cr.pdf"><date notBefore="2014-12-16"></date></ref></edition><respStmt><resp>contributor</resp><name key="168231"><persName><forename>Victor</forename><surname>Codocedo</surname></persName><email>victor.codocedo@inria.fr</email></name></respStmt></editionStmt><publicationStmt><distributor>CCSD</distributor><idno type="halId">hal-01095884</idno><idno type="halUri">https://hal.inria.fr/hal-01095884</idno><idno type="halBibtex">codocedo:hal-01095884</idno><idno type="halRefHtml">What formal concept analysis can do for artificial intelligence? (FCA4AI 2014) Workshop at ECAI 2014, Aug 2014, Prague, Czech Republic. 2014</idno><idno type="halRef">What formal concept analysis can do for artificial intelligence? (FCA4AI 2014) Workshop at ECAI 2014, Aug 2014, Prague, Czech Republic. 2014</idno></publicationStmt><seriesStmt><idno type="stamp" n="CNRS">CNRS - Centre national de la recherche scientifique</idno><idno type="stamp" n="INRIA">INRIA - Institut National de Recherche en Informatique et en Automatique</idno><idno type="stamp" n="INRIA-LORRAINE">INRIA Nancy - Grand Est</idno><idno type="stamp" n="LORIA2">Publications du LORIA</idno><idno type="stamp" n="INRIA-NANCY-GRAND-EST">INRIA Nancy - Grand Est</idno><idno type="stamp" n="LORIA-TALC" p="LORIA">Traitement automatique des langues et des connaissances</idno><idno type="stamp" n="UNIV-LORRAINE">Université de Lorraine</idno><idno type="stamp" n="LORIA">LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications</idno><idno type="stamp" n="INRIA_TEST">INRIA - Institut National de Recherche en Informatique et en Automatique</idno></seriesStmt><notesStmt><note type="audience" n="2">International</note><note type="invited" n="0">No</note><note type="popular" n="0">No</note><note type="peer" n="1">Yes</note><note type="proceedings" n="1">Yes</note></notesStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Bicluster enumeration using Formal Concept Analysis</title><author role="aut"><persName><forename type="first">Victor</forename><surname>Codocedo</surname></persName><email>victor.codocedo@loria.fr</email><idno type="halAuthorId">1125631</idno><affiliation ref="#struct-205125"></affiliation></author><author role="aut"><persName><forename type="first">Amedeo</forename><surname>Napoli</surname></persName><email>Amedeo.Napoli@loria.fr</email><idno type="halAuthorId">61765</idno><affiliation ref="#struct-205125"></affiliation></author></analytic><monogr><meeting><title>What formal concept analysis can do for artificial intelligence? (FCA4AI 2014) Workshop at ECAI 2014</title><date type="start">2014-08-09</date><date type="end">2014-08-09</date><settlement>Prague</settlement><country key="CZ">Czech Republic</country></meeting><imprint><date type="datePub">2014-08-19</date></imprint></monogr></biblStruct></sourceDesc><profileDesc><langUsage><language ident="en">English</language></langUsage><textClass><keywords scheme="author"><term xml:lang="en">formal concept analysis</term><term xml:lang="en">biclustering</term><term xml:lang="en">pattern structures</term></keywords><classCode scheme="halDomain" n="info.info-ds">Computer Science [cs]/Data Structures and Algorithms [cs.DS]</classCode><classCode scheme="halDomain" n="info.info-it">Computer Science [cs]/Information Theory [cs.IT]</classCode><classCode scheme="halTypology" n="COMM">Conference papers</classCode></textClass><abstract xml:lang="en">In this work we introduce a novel technique to enumerate constant row/column value biclusters using formal concept analysis. To achieve this, a numerical data-table (standard input for biclustering al-gorithms) is modelled as a many-valued context where rows represent objects and columns represent attributes. Using equivalence relations de-fined for each single column, we are able to translate the bicluster mining problem in terms of the partition pattern structure framework. We show how biclustering can benefit from the FCA framework through its ro-bust theoretical description and efficient algorithms. Finally, we show how this technique is able to find high quality biclusters (in terms of the mean squared error) more efficiently than a state-of-the-art bicluster algorithm.</abstract></profileDesc></hal></record>Pour manipuler ce document sous Unix (Dilib)
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