Datasets for the Evaluation of Substitution-Tolerant Subgraph Isomorphism
Identifieur interne : 000086 ( Hal/Corpus ); précédent : 000085; suivant : 000087Datasets for the Evaluation of Substitution-Tolerant Subgraph Isomorphism
Auteurs : Pierre Héroux ; Pierre Le Bodic ; Sébastien AdamSource :
Abstract
Due to their representative power, structural descriptions have gained a great interest in the community working on graphics recognition. Indeed, graph based representations have successful been used for isolated symbol recognition. New challenges in this research field have focused on symbol recognition, symbol spotting or symbol based indexing of technical drawing. When they are based on structural descriptions, these tasks can be expressed by means of a subgraph isomorphism search. Indeed, in consists in locating the instance of a pattern graph representing a symbol in a target graph representing the whole document image. However, there is a lack of publicly available datasets allowing to evaluate the performance of subgraph isomorphism approaches in presence of noisy data. In this paper, we present three datasets that can be used to evaluate the performance of algorithms on several tasks involving subgraph isomorphism. Two of these datasets have been synthetically generated and allow to evaluate the search of a single instance of the pattern with or without perturbed labels. The third dataset corresponds to the structural description of architectural plans and allows to evaluate the search of multiple occurrences of the pattern. These datasets are made available for download. We also propose several measures to qualify each of the tasks.
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76821 Mont-Saint-Aignan</addrLine><country key="FR"></country></address><ref type="url">http://www.univ-rouen.fr/</ref></desc></org></tutelle><tutelle active="#struct-301288" type="indirect"><org type="department" xml:id="struct-301288" status="VALID"><orgName>Institut National des Sciences Appliquées - Rouen</orgName><orgName type="acronym">INSA Rouen</orgName><desc><address><country key="FR"></country></address></desc><listRelation><relation active="#struct-301232" type="direct"></relation></listRelation></org></tutelle><tutelle active="#struct-301232" type="indirect"><org type="institution" xml:id="struct-301232" status="VALID"><orgName>Institut National des Sciences Appliquées</orgName><orgName type="acronym">INSA</orgName><desc><address><country key="FR"></country></address></desc></org></tutelle></tutelles></hal:affiliation></affiliation></author></analytic></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Due to their representative power, structural descriptions have gained a great interest in the community working on graphics recognition. Indeed, graph based representations have successful been used for isolated symbol recognition. New challenges in this research field have focused on symbol recognition, symbol spotting or symbol based indexing of technical drawing. When they are based on structural descriptions, these tasks can be expressed by means of a subgraph isomorphism search. Indeed, in consists in locating the instance of a pattern graph representing a symbol in a target graph representing the whole document image. However, there is a lack of publicly available datasets allowing to evaluate the performance of subgraph isomorphism approaches in presence of noisy data. In this paper, we present three datasets that can be used to evaluate the performance of algorithms on several tasks involving subgraph isomorphism. Two of these datasets have been synthetically generated and allow to evaluate the search of a single instance of the pattern with or without perturbed labels. The third dataset corresponds to the structural description of architectural plans and allows to evaluate the search of multiple occurrences of the pattern. These datasets are made available for download. We also propose several measures to qualify each of the tasks.</div></front></TEI><hal api="V3"><titleStmt><title xml:lang="en">Datasets for the Evaluation of Substitution-Tolerant Subgraph Isomorphism</title><author role="aut"><persName><forename type="first">Pierre</forename><surname>Héroux</surname></persName><email>Pierre.Heroux@univ-rouen.fr</email><idno type="idhal">pierreheroux</idno><idno type="halauthor">145403</idno><affiliation ref="#struct-389520"></affiliation></author><author role="aut"><persName><forename type="first">Pierre</forename><surname>Le Bodic</surname></persName><email></email><idno type="halauthor">694110</idno><affiliation ref="#struct-29428"></affiliation></author><author role="aut"><persName><forename type="first">Sébastien</forename><surname>Adam</surname></persName><email>Sbastien.Adam@univ-rouen.fr</email><idno type="halauthor">145405</idno><affiliation ref="#struct-389520"></affiliation></author><editor role="depositor"><persName><forename>Pierre</forename><surname>Héroux</surname></persName><email>Pierre.Heroux@univ-rouen.fr</email></editor></titleStmt><editionStmt><edition n="v1" type="current"><date type="whenSubmitted">2014-01-22 12:09:35</date><date type="whenWritten">2013</date><date type="whenModified">2015-05-19 16:30:00</date><date type="whenReleased">2014-01-28 16:10:19</date><date type="whenProduced">2013</date><date type="whenEndEmbargoed">2014-01-22</date><ref type="file" target="https://hal.archives-ouvertes.fr/hal-00934597/document"><date notBefore="2014-01-22"></date></ref><ref type="file" subtype="author" n="1" target="https://hal.archives-ouvertes.fr/hal-00934597/file/grec2013.pdf"><date notBefore="2014-01-22"></date></ref></edition><respStmt><resp>contributor</resp><name key="114396"><persName><forename>Pierre</forename><surname>Héroux</surname></persName><email>Pierre.Heroux@univ-rouen.fr</email></name></respStmt></editionStmt><publicationStmt><distributor>CCSD</distributor><idno type="halId">hal-00934597</idno><idno type="halUri">https://hal.archives-ouvertes.fr/hal-00934597</idno><idno type="halBibtex">heroux:hal-00934597</idno><idno type="halRefHtml">IAPR International Workshop on Graphics Recognition, 2013, Lehigh, France</idno><idno type="halRef">IAPR International Workshop on Graphics Recognition, 2013, Lehigh, France</idno></publicationStmt><seriesStmt><idno type="stamp" n="UNIV-LEHAVRE">Université du Havre</idno><idno type="stamp" n="UNIV-ROUEN">Université de Rouen</idno><idno type="stamp" n="LITIS">Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes</idno><idno type="stamp" n="COMUE-NORMANDIE">Normandie Université</idno></seriesStmt><notesStmt><note type="audience" n="1">Not set</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="0">No</note></notesStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Datasets for the Evaluation of Substitution-Tolerant Subgraph Isomorphism</title><author role="aut"><persName><forename type="first">Pierre</forename><surname>Héroux</surname></persName><email>Pierre.Heroux@univ-rouen.fr</email><idno type="idHal">pierreheroux</idno><idno type="halAuthorId">145403</idno><affiliation ref="#struct-389520"></affiliation></author><author role="aut"><persName><forename type="first">Pierre</forename><surname>Le Bodic</surname></persName><idno type="halAuthorId">694110</idno><affiliation ref="#struct-29428"></affiliation></author><author role="aut"><persName><forename type="first">Sébastien</forename><surname>Adam</surname></persName><email>Sbastien.Adam@univ-rouen.fr</email><idno type="halAuthorId">145405</idno><affiliation ref="#struct-389520"></affiliation></author></analytic><monogr><meeting><title>IAPR International Workshop on Graphics Recognition</title><date type="start">2013</date><settlement>Lehigh</settlement><country key="FR">France</country></meeting><imprint></imprint></monogr></biblStruct></sourceDesc><profileDesc><langUsage><language ident="en">English</language></langUsage><textClass><classCode scheme="halDomain" n="info.info-tt">Computer Science [cs]/Document and Text Processing</classCode><classCode scheme="halTypology" n="COMM">Conference papers</classCode></textClass><abstract xml:lang="en">Due to their representative power, structural descriptions have gained a great interest in the community working on graphics recognition. Indeed, graph based representations have successful been used for isolated symbol recognition. New challenges in this research field have focused on symbol recognition, symbol spotting or symbol based indexing of technical drawing. When they are based on structural descriptions, these tasks can be expressed by means of a subgraph isomorphism search. Indeed, in consists in locating the instance of a pattern graph representing a symbol in a target graph representing the whole document image. However, there is a lack of publicly available datasets allowing to evaluate the performance of subgraph isomorphism approaches in presence of noisy data. In this paper, we present three datasets that can be used to evaluate the performance of algorithms on several tasks involving subgraph isomorphism. Two of these datasets have been synthetically generated and allow to evaluate the search of a single instance of the pattern with or without perturbed labels. The third dataset corresponds to the structural description of architectural plans and allows to evaluate the search of multiple occurrences of the pattern. These datasets are made available for download. We also propose several measures to qualify each of the tasks.</abstract></profileDesc></hal></record>Pour manipuler ce document sous Unix (Dilib)
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