Constructing Iceberg Lattices from Frequent Closures Using Generators
Identifieur interne : 003C75 ( Istex/Corpus ); précédent : 003C74; suivant : 003C76Constructing Iceberg Lattices from Frequent Closures Using Generators
Auteurs : Laszlo Szathmary ; Petko Valtchev ; Amedeo Napoli ; Robert GodinSource :
- Lecture Notes in Computer Science [ 0302-9743 ]
Abstract
Abstract: Frequent closures (FCIs) and generators (FGs) as well as the precedence relation on FCIs are key components in the definition of a variety of association rule bases. Although their joint computation has been studied in concept analysis, no scalable algorithm exists for the task at present. We propose here to reverse a method from the latter field using a fundamental property of hypergraph theory. The goal is to extract the precedence relation from a more common mining output, i.e. closures and generators. The resulting order computation algorithm proves to be highly efficient, benefiting from peculiarities of generator families in typical mining datasets. Due to its genericity, the new algorithm fits an arbitrary FCI/FG-miner.
Url:
DOI: 10.1007/978-3-540-88411-8_15
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ISTEX:FD327584191AC45B256A788DD3B5832EFEC9B63ELe document en format XML
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We propose here to reverse a method from the latter field using a fundamental property of hypergraph theory. The goal is to extract the precedence relation from a more common mining output, i.e. closures and generators. The resulting order computation algorithm proves to be highly efficient, benefiting from peculiarities of generator families in typical mining datasets. Due to its genericity, the new algorithm fits an arbitrary FCI/FG-miner.</div></front></TEI><istex><corpusName>springer-ebooks</corpusName><author><json:item><name>Laszlo Szathmary</name><affiliations><json:string>Dépt. d’Informatique UQAM, C.P. 8888, Succ. Centre-Ville, H3C 3P8, Montréal, Canada</json:string><json:string>E-mail: Szathmary.L@gmail.com</json:string></affiliations></json:item><json:item><name>Petko Valtchev</name><affiliations><json:string>Dépt. d’Informatique UQAM, C.P. 8888, Succ. 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Proceedings</BookSubTitle><BookVolumeNumber>5255</BookVolumeNumber><BookSequenceNumber>5255</BookSequenceNumber><BookDOI>10.1007/978-3-540-88411-8</BookDOI><BookTitleID>183320</BookTitleID><BookPrintISBN>978-3-540-88410-1</BookPrintISBN><BookElectronicISBN>978-3-540-88411-8</BookElectronicISBN><BookChapterCount>31</BookChapterCount><BookCopyright><CopyrightHolderName>Springer Berlin Heidelberg</CopyrightHolderName><CopyrightYear>2008</CopyrightYear></BookCopyright><BookSubjectGroup><BookSubject Code="I" Type="Primary">Computer Science</BookSubject><BookSubject Code="I21017" Priority="1" Type="Secondary">Artificial Intelligence (incl. Robotics)</BookSubject><BookSubject Code="I18024" Priority="2" Type="Secondary">Database Management</BookSubject><BookSubject Code="I18032" Priority="3" Type="Secondary">Information Storage and Retrieval</BookSubject><BookSubject Code="I18030" Priority="4" Type="Secondary">Data Mining and Knowledge Discovery</BookSubject><BookSubject Code="I2301X" Priority="5" Type="Secondary">Computer Appl. in Administrative Data Processing</BookSubject><BookSubject Code="I23028" Priority="6" Type="Secondary">Computer Appl. in Social and Behavioral Sciences</BookSubject><SubjectCollection Code="SUCO11645">Computer Science</SubjectCollection></BookSubjectGroup></BookInfo><BookHeader><EditorGroup><Editor AffiliationIDS="Aff1"><EditorName DisplayOrder="Western"><GivenName>Jean-François</GivenName><FamilyName>Boulicaut</FamilyName></EditorName><Contact><Email>jean-francois.boulicaut@liris.cnrs.fr</Email></Contact></Editor><Editor AffiliationIDS="Aff2"><EditorName DisplayOrder="Western"><GivenName>Michael</GivenName><GivenName>R.</GivenName><FamilyName>Berthold</FamilyName></EditorName><Contact><Email>Michael.Berthold@uni-Konstanz.de</Email></Contact></Editor><Editor AffiliationIDS="Aff3"><EditorName DisplayOrder="Western"><GivenName>Tamás</GivenName><FamilyName>Horváth</FamilyName></EditorName><Contact><Email>tamas.horvath@iais.fraunhofer.de</Email></Contact></Editor><Affiliation ID="Aff1"><OrgName>INSA-Lyon, LIRIS CNRS UMR5205</OrgName><OrgAddress><Postcode>F-69621</Postcode><City>Villeurbanne</City><Country>France</Country></OrgAddress></Affiliation><Affiliation ID="Aff2"><OrgDivision>Department of Computer and Information Science</OrgDivision><OrgName>University of Konstanz</OrgName><OrgAddress><Postbox>Box M 712</Postbox><Postcode>78457</Postcode><City>Konstanz</City><Country>Germany</Country></OrgAddress></Affiliation><Affiliation ID="Aff3"><OrgName>Fraunhofer IAIS, Schloss Birlinghoven</OrgName><OrgAddress><City>Sankt Augustin</City><Country>Germany</Country></OrgAddress></Affiliation></EditorGroup></BookHeader><Part ID="Part4"><PartInfo TocLevels="0"><PartID>4</PartID><PartSequenceNumber>4</PartSequenceNumber><PartTitle>Associations</PartTitle><PartChapterCount>2</PartChapterCount><PartContext><SeriesID>558</SeriesID><BookTitle>Discovery Science</BookTitle></PartContext></PartInfo><Chapter ID="Chap15" Language="En"><ChapterInfo ChapterType="OriginalPaper" ContainsESM="No" NumberingStyle="Unnumbered" TocLevels="0"><ChapterID>15</ChapterID><ChapterDOI>10.1007/978-3-540-88411-8_15</ChapterDOI><ChapterSequenceNumber>15</ChapterSequenceNumber><ChapterTitle Language="En">Constructing Iceberg Lattices from Frequent Closures Using Generators</ChapterTitle><ChapterFirstPage>136</ChapterFirstPage><ChapterLastPage>147</ChapterLastPage><ChapterCopyright><CopyrightHolderName>Springer-Verlag Berlin Heidelberg</CopyrightHolderName><CopyrightYear>2008</CopyrightYear></ChapterCopyright><ChapterGrants Type="Regular"><MetadataGrant Grant="OpenAccess"></MetadataGrant><AbstractGrant Grant="OpenAccess"></AbstractGrant><BodyPDFGrant Grant="Restricted"></BodyPDFGrant><BodyHTMLGrant Grant="Restricted"></BodyHTMLGrant><BibliographyGrant Grant="Restricted"></BibliographyGrant><ESMGrant Grant="Restricted"></ESMGrant></ChapterGrants><ChapterContext><SeriesID>558</SeriesID><PartID>4</PartID><BookID>978-3-540-88411-8</BookID><BookTitle>Discovery Science</BookTitle></ChapterContext></ChapterInfo><ChapterHeader><AuthorGroup><Author AffiliationIDS="Aff4"><AuthorName DisplayOrder="Western"><GivenName>Laszlo</GivenName><FamilyName>Szathmary</FamilyName></AuthorName><Contact><Email>Szathmary.L@gmail.com</Email></Contact></Author><Author AffiliationIDS="Aff4"><AuthorName DisplayOrder="Western"><GivenName>Petko</GivenName><FamilyName>Valtchev</FamilyName></AuthorName><Contact><Email>valtchev.petko@uqam.ca</Email></Contact></Author><Author AffiliationIDS="Aff5"><AuthorName DisplayOrder="Western"><GivenName>Amedeo</GivenName><FamilyName>Napoli</FamilyName></AuthorName><Contact><Email>napoli@loria.fr</Email></Contact></Author><Author AffiliationIDS="Aff4"><AuthorName DisplayOrder="Western"><GivenName>Robert</GivenName><FamilyName>Godin</FamilyName></AuthorName><Contact><Email>godin.robert@uqam.ca</Email></Contact></Author><Affiliation ID="Aff4"><OrgName>Dépt. d’Informatique UQAM</OrgName><OrgAddress><Street>C.P. 8888, Succ. Centre-Ville</Street><City>Montréal</City><Postcode>H3C 3P8</Postcode><Country>Canada</Country></OrgAddress></Affiliation><Affiliation ID="Aff5"><OrgName>LORIA UMR 7503</OrgName><OrgAddress><Postbox>B.P. 239</Postbox><Postcode>54506</Postcode><City>Vandœuvre-lès-Nancy Cedex</City><Country>France</Country></OrgAddress></Affiliation></AuthorGroup><Abstract ID="Abs1" Language="En"><Heading>Abstract</Heading><Para>Frequent closures (FCIs) and generators (FGs) as well as the precedence relation on FCIs are key components in the definition of a variety of association rule bases. Although their joint computation has been studied in concept analysis, no scalable algorithm exists for the task at present. We propose here to reverse a method from the latter field using a fundamental property of hypergraph theory. The goal is to extract the precedence relation from a more common mining output, i.e. closures and generators. The resulting order computation algorithm proves to be highly efficient, benefiting from peculiarities of generator families in typical mining datasets. Due to its genericity, the new algorithm fits an arbitrary FCI/FG-miner.</Para></Abstract></ChapterHeader><NoBody></NoBody></Chapter></Part></Book></Series></Publisher></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>Constructing Iceberg Lattices from Frequent Closures Using Generators</title></titleInfo><titleInfo type="alternative" contentType="CDATA"><title>Constructing Iceberg Lattices from Frequent Closures Using Generators</title></titleInfo><name type="personal"><namePart type="given">Laszlo</namePart><namePart type="family">Szathmary</namePart><affiliation>Dépt. d’Informatique UQAM, C.P. 8888, Succ. Centre-Ville, H3C 3P8, Montréal, Canada</affiliation><affiliation>E-mail: Szathmary.L@gmail.com</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Petko</namePart><namePart type="family">Valtchev</namePart><affiliation>Dépt. d’Informatique UQAM, C.P. 8888, Succ. Centre-Ville, H3C 3P8, Montréal, Canada</affiliation><affiliation>E-mail: valtchev.petko@uqam.ca</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Amedeo</namePart><namePart type="family">Napoli</namePart><affiliation>LORIA UMR 7503, B.P. 239, 54506, Vandœuvre-lès-Nancy Cedex, France</affiliation><affiliation>E-mail: napoli@loria.fr</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Robert</namePart><namePart type="family">Godin</namePart><affiliation>Dépt. d’Informatique UQAM, C.P. 8888, Succ. Centre-Ville, H3C 3P8, Montréal, Canada</affiliation><affiliation>E-mail: godin.robert@uqam.ca</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre displayLabel="OriginalPaper" authority="ISTEX" authorityURI="https://content-type.data.istex.fr" type="conference" valueURI="https://content-type.data.istex.fr/ark:/67375/XTP-BFHXPBJJ-3">conference</genre><originInfo><publisher>Springer Berlin Heidelberg</publisher><place><placeTerm type="text">Berlin, Heidelberg</placeTerm></place><dateIssued encoding="w3cdtf">2008</dateIssued><copyrightDate encoding="w3cdtf">2008</copyrightDate></originInfo><language><languageTerm type="code" authority="rfc3066">en</languageTerm><languageTerm type="code" authority="iso639-2b">eng</languageTerm></language><abstract lang="en">Abstract: Frequent closures (FCIs) and generators (FGs) as well as the precedence relation on FCIs are key components in the definition of a variety of association rule bases. Although their joint computation has been studied in concept analysis, no scalable algorithm exists for the task at present. We propose here to reverse a method from the latter field using a fundamental property of hypergraph theory. The goal is to extract the precedence relation from a more common mining output, i.e. closures and generators. The resulting order computation algorithm proves to be highly efficient, benefiting from peculiarities of generator families in typical mining datasets. Due to its genericity, the new algorithm fits an arbitrary FCI/FG-miner.</abstract><relatedItem type="host"><titleInfo><title>Discovery Science</title><subTitle>11th International Conference, DS 2008, Budapest, Hungary, October 13-16, 2008. Proceedings</subTitle></titleInfo><name type="personal"><namePart type="given">Jean-François</namePart><namePart type="family">Boulicaut</namePart><affiliation>INSA-Lyon, LIRIS CNRS UMR5205, F-69621, Villeurbanne, France</affiliation><affiliation>E-mail: jean-francois.boulicaut@liris.cnrs.fr</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Michael</namePart><namePart type="given">R.</namePart><namePart type="family">Berthold</namePart><affiliation>Department of Computer and Information Science, University of Konstanz, Box M 712, 78457, Konstanz, Germany</affiliation><affiliation>E-mail: Michael.Berthold@uni-Konstanz.de</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Tamás</namePart><namePart type="family">Horváth</namePart><affiliation>Fraunhofer IAIS, Schloss Birlinghoven, Sankt Augustin, Germany</affiliation><affiliation>E-mail: tamas.horvath@iais.fraunhofer.de</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><genre type="book-series" authority="ISTEX" authorityURI="https://publication-type.data.istex.fr" valueURI="https://publication-type.data.istex.fr/ark:/67375/JMC-0G6R5W5T-Z">book-series</genre><originInfo><publisher>Springer</publisher><copyrightDate encoding="w3cdtf">2008</copyrightDate><issuance>monographic</issuance></originInfo><subject><genre>Book-Subject-Collection</genre><topic authority="SpringerSubjectCodes" authorityURI="SUCO11645">Computer Science</topic></subject><subject><genre>Book-Subject-Group</genre><topic authority="SpringerSubjectCodes" authorityURI="I">Computer Science</topic><topic authority="SpringerSubjectCodes" authorityURI="I21017">Artificial Intelligence (incl. Robotics)</topic><topic authority="SpringerSubjectCodes" authorityURI="I18024">Database Management</topic><topic authority="SpringerSubjectCodes" authorityURI="I18032">Information Storage and Retrieval</topic><topic authority="SpringerSubjectCodes" authorityURI="I18030">Data Mining and Knowledge Discovery</topic><topic authority="SpringerSubjectCodes" authorityURI="I2301X">Computer Appl. in Administrative Data Processing</topic><topic authority="SpringerSubjectCodes" authorityURI="I23028">Computer Appl. in Social and Behavioral Sciences</topic></subject><identifier type="DOI">10.1007/978-3-540-88411-8</identifier><identifier type="ISBN">978-3-540-88410-1</identifier><identifier type="eISBN">978-3-540-88411-8</identifier><identifier type="ISSN">0302-9743</identifier><identifier type="eISSN">1611-3349</identifier><identifier type="BookTitleID">183320</identifier><identifier type="BookID">978-3-540-88411-8</identifier><identifier type="BookChapterCount">31</identifier><identifier type="BookVolumeNumber">5255</identifier><identifier type="BookSequenceNumber">5255</identifier><identifier type="PartChapterCount">2</identifier><part><date>2008</date><detail type="part"><title>Associations</title></detail><detail type="volume"><number>5255</number><caption>vol.</caption></detail><extent unit="pages"><start>136</start><end>147</end></extent></part><recordInfo><recordOrigin>Springer Berlin Heidelberg, 2008</recordOrigin></recordInfo></relatedItem><relatedItem type="series"><titleInfo><title>Lecture Notes in Computer Science</title></titleInfo><originInfo><publisher>Springer</publisher><copyrightDate encoding="w3cdtf">2008</copyrightDate><issuance>serial</issuance></originInfo><relatedItem type="constituent"><titleInfo><title>Lecture Notes in Artificial Intelligence</title></titleInfo><name type="personal"><namePart type="given">Jaime</namePart><namePart type="given">G.</namePart><namePart type="family">Carbonell</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Jörg</namePart><namePart type="family">Siekmann</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Jean-François</namePart><namePart type="family">Boulicaut</namePart><affiliation>INSA-Lyon, LIRIS CNRS UMR5205, F-69621, Villeurbanne, France</affiliation><affiliation>E-mail: jean-francois.boulicaut@liris.cnrs.fr</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Michael</namePart><namePart type="given">R.</namePart><namePart type="family">Berthold</namePart><affiliation>Department of Computer and Information Science, University of Konstanz, Box M 712, 78457, Konstanz, Germany</affiliation><affiliation>E-mail: Michael.Berthold@uni-Konstanz.de</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Tamás</namePart><namePart type="family">Horváth</namePart><affiliation>Fraunhofer IAIS, Schloss Birlinghoven, Sankt Augustin, Germany</affiliation><affiliation>E-mail: tamas.horvath@iais.fraunhofer.de</affiliation><role><roleTerm type="text">editor</roleTerm></role></name><genre type="sub-series"></genre><identifier type="ISSN">0302-9743</identifier><identifier type="eISSN">1611-3349</identifier><identifier type="SubSeriesID">1244</identifier></relatedItem><identifier type="ISSN">0302-9743</identifier><identifier type="eISSN">1611-3349</identifier><identifier type="SeriesID">558</identifier><recordInfo><recordOrigin>Springer Berlin Heidelberg, 2008</recordOrigin></recordInfo></relatedItem><identifier type="istex">FD327584191AC45B256A788DD3B5832EFEC9B63E</identifier><identifier type="ark">ark:/67375/HCB-QQQ8NJ71-B</identifier><identifier type="DOI">10.1007/978-3-540-88411-8_15</identifier><identifier type="ChapterID">15</identifier><identifier type="ChapterID">Chap15</identifier><accessCondition type="use and reproduction" contentType="copyright">Springer Berlin Heidelberg, 2008</accessCondition><recordInfo><recordContentSource authority="ISTEX" authorityURI="https://loaded-corpus.data.istex.fr" valueURI="https://loaded-corpus.data.istex.fr/ark:/67375/XBH-RLRX46XW-4">springer</recordContentSource><recordOrigin>Springer-Verlag Berlin Heidelberg, 2008</recordOrigin></recordInfo></mods><json:item><extension>json</extension><original>false</original><mimetype>application/json</mimetype><uri>https://api.istex.fr/ark:/67375/HCB-QQQ8NJ71-B/record.json</uri></json:item></metadata></istex></record>Pour manipuler ce document sous Unix (Dilib)
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