Implicit and Explicit Graph Embedding: Comparison of both Approaches on Chemoinformatics Applications
Identifieur interne : 001860 ( Main/Exploration ); précédent : 001859; suivant : 001861Implicit and Explicit Graph Embedding: Comparison of both Approaches on Chemoinformatics Applications
Auteurs : Benoit Gaüzère [France] ; Hasegawa Makoto [France] ; Luc Brun [France] ; Salvatore Tabbone [France]Source :
English descriptors
- mix :
Abstract
Defining similarities or distances between graphs is one of the bases of the structural pattern recognition field. An important trend within this field consists in going beyond the simple formulation of simi- larity measures by studying properties of graph's spaces induced by such distance or similarity measures . Such a problematic is closely related to the graph embedding problem. In this article, we investigate two types of similarity measures. The first one is based on the notion of graph edit distance which aims to catch a global dissimilarity between graphs. The second family is based on comparisons of bags of patterns extracted from graphs to be compared. Both approaches are detailed and their performances are evaluated on different chemoinformatics problems.
Url:
DOI: 10.1007/978-3-642-34166-3_56
Affiliations:
- France
- Basse-Normandie, Grand Est, Lorraine (région), Région Normandie
- Caen, Metz, Nancy
- Université de Caen Basse-Normandie, Université de Lorraine
Links toward previous steps (curation, corpus...)
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- to stream Hal, to step Checkpoint: 001476
- to stream Main, to step Merge: 001888
- to stream Main, to step Curation: 001860
Le document en format XML
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NLPKD</orgName><desc><address><country key="FR"></country></address><ref type="url">http://www.loria.fr/la-recherche-en/departements/Knowledge-and-Language-Management</ref></desc><listRelation><relation active="#struct-206040" type="direct"></relation><relation active="#struct-300009" type="indirect"></relation><relation active="#struct-413289" type="indirect"></relation><relation name="UMR7503" active="#struct-441569" type="indirect"></relation></listRelation></org></tutelle><tutelle active="#struct-206040" type="indirect"><org type="laboratory" xml:id="struct-206040" status="VALID"><idno type="IdRef">067077927</idno><idno type="RNSR">198912571S</idno><idno type="IdUnivLorraine">[UL]RSI--</idno><orgName>Laboratoire Lorrain de Recherche en Informatique et ses Applications</orgName><orgName type="acronym">LORIA</orgName><date type="start">2012-01-01</date><desc><address><addrLine>Campus Scientifique BP 239 54506 Vandoeuvre-lès-Nancy Cedex</addrLine><country key="FR"></country></address><ref type="url">http://www.loria.fr</ref></desc><listRelation><relation active="#struct-300009" type="direct"></relation><relation active="#struct-413289" type="direct"></relation><relation name="UMR7503" active="#struct-441569" type="direct"></relation></listRelation></org></tutelle><tutelle active="#struct-300009" type="indirect"><org type="institution" xml:id="struct-300009" status="VALID"><orgName>Institut National de Recherche en Informatique et en Automatique</orgName><orgName type="acronym">Inria</orgName><desc><address><addrLine>Domaine de VoluceauRocquencourt - BP 10578153 Le Chesnay Cedex</addrLine><country key="FR"></country></address><ref type="url">http://www.inria.fr/en/</ref></desc></org></tutelle><tutelle active="#struct-413289" type="indirect"><org type="institution" xml:id="struct-413289" status="VALID"><idno type="IdRef">157040569</idno><idno type="IdUnivLorraine">[UL]100--</idno><orgName>Université de Lorraine</orgName><orgName type="acronym">UL</orgName><date type="start">2012-01-01</date><desc><address><addrLine>34 cours Léopold - CS 25233 - 54052 Nancy cedex</addrLine><country key="FR"></country></address><ref type="url">http://www.univ-lorraine.fr/</ref></desc></org></tutelle><tutelle name="UMR7503" active="#struct-441569" type="indirect"><org type="institution" xml:id="struct-441569" status="VALID"><idno type="IdRef">02636817X</idno><idno type="ISNI">0000000122597504</idno><orgName>Centre National de la Recherche Scientifique</orgName><orgName type="acronym">CNRS</orgName><date type="start">1939-10-19</date><desc><address><country key="FR"></country></address><ref type="url">http://www.cnrs.fr/</ref></desc></org></tutelle></tutelles></hal:affiliation><country>France</country><placeName><settlement type="city">Nancy</settlement><settlement type="city">Metz</settlement><region type="region" nuts="2">Grand Est</region><region type="old region" nuts="2">Lorraine (région)</region></placeName><orgName type="university">Université de Lorraine</orgName></affiliation></author></analytic><idno type="DOI">10.1007/978-3-642-34166-3_56</idno></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="mix" xml:lang="en"><term>Explicit</term><term>implicit embedding</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Defining similarities or distances between graphs is one of the bases of the structural pattern recognition field. An important trend within this field consists in going beyond the simple formulation of simi- larity measures by studying properties of graph's spaces induced by such distance or similarity measures . Such a problematic is closely related to the graph embedding problem. In this article, we investigate two types of similarity measures. The first one is based on the notion of graph edit distance which aims to catch a global dissimilarity between graphs. The second family is based on comparisons of bags of patterns extracted from graphs to be compared. Both approaches are detailed and their performances are evaluated on different chemoinformatics problems.</div></front></TEI><affiliations><list><country><li>France</li></country><region><li>Basse-Normandie</li><li>Grand Est</li><li>Lorraine (région)</li><li>Région Normandie</li></region><settlement><li>Caen</li><li>Metz</li><li>Nancy</li></settlement><orgName><li>Université de Caen Basse-Normandie</li><li>Université de Lorraine</li></orgName></list><tree><country name="France"><region name="Région Normandie"><name sortKey="Gauzere, Benoit" sort="Gauzere, Benoit" uniqKey="Gauzere B" first="Benoit" last="Gaüzère">Benoit Gaüzère</name></region><name sortKey="Brun, Luc" sort="Brun, Luc" uniqKey="Brun L" first="Luc" last="Brun">Luc Brun</name><name sortKey="Makoto, Hasegawa" sort="Makoto, Hasegawa" uniqKey="Makoto H" first="Hasegawa" last="Makoto">Hasegawa Makoto</name><name sortKey="Tabbone, Salvatore" sort="Tabbone, Salvatore" uniqKey="Tabbone S" first="Salvatore" last="Tabbone">Salvatore Tabbone</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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