untitled
<OAI-PMH schemaLocation=http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd>
<responseDate>2018-01-15T15:42:56Z</responseDate>
<request identifier=oai:HAL:hal-00327782v1 verb=GetRecord metadataPrefix=oai_dc>http://api.archives-ouvertes.fr/oai/hal/</request>
<GetRecord>
<record>
<header>
<identifier>oai:HAL:hal-00327782v1</identifier>
<datestamp>2017-12-21</datestamp>
<setSpec>type:COMM</setSpec>
<setSpec>subject:info</setSpec>
<setSpec>collection:UNIV-AG</setSpec>
<setSpec>collection:BNRMI</setSpec>
<setSpec>collection:CEREGMIA</setSpec>
</header>
<metadata><dc>
<publisher>HAL CCSD</publisher>
<title lang=en>Soft Uncoupling of Markov Chains for Permeable Language Distinction: A New Algorithm</title>
<creator>Nock, Richard</creator>
<creator>Vaillant, Pascal</creator>
<creator>Nielsen, Frank</creator>
<creator>Henry, Claudia</creator>
<contributor>Centre de Recherche en Economie, Gestion, Modélisation et Informatique Appliquée (CEREGMIA) ; Université des Antilles et de la Guyane (UAG)</contributor>
<contributor>Groupe de Recherche en Informatique et Mathématiques Appliquées Antilles-Guyane (GRIMAAG) ; Université des Antilles et de la Guyane (UAG)</contributor>
<contributor>Sony Computer Science Laboratory Paris (SONY CSL-Paris) ; Sony</contributor>
<contributor>ACI Jeunes Chercheurs JC 9009, 2003-2006 (Ministère de l'Enseignement Supérieur et de la Recherche, Fonds National pour la Science) : « Nouveaux paradigmes de classification : aspects théoriques et application à l'acquisition de connaissances » (Richard Nock, Pascal Vaillant)</contributor>
<description>6 pages, 7 embedded figures, LaTeX 2e using the ecai2006.cls document class and the algorithm2e.sty style file (+ standard packages like epsfig, amsmath, amssymb, amsfonts...). Extends the short version contained in the ECAI 2006 proceedings.</description>
<description>International audience</description>
<source>ECAI 2006: 17th European Conference on Artificial Intelligence</source>
<source>17th European Conference on Artificial Intelligence (ECAI 2006)</source>
<coverage>Riva del Garda, Italy</coverage>
<contributor>Gerhard Brewka, Silvia Coradeschi, Anna Perini et Paolo Traverso</contributor>
<publisher>IOS Press (Amsterdam)</publisher>
<identifier>hal-00327782</identifier>
<identifier>https://hal.archives-ouvertes.fr/hal-00327782</identifier>
<source>https://hal.archives-ouvertes.fr/hal-00327782</source>
<source>Gerhard Brewka, Silvia Coradeschi, Anna Perini et Paolo Traverso. 17th European Conference on Artificial Intelligence (ECAI 2006), Aug 2006, Riva del Garda, Italy. IOS Press (Amsterdam), ISBN 1-58603-642-3, p. 823-824, 2006, Frontiers in Artificial Intelligence and Applications</source>
<identifier>ARXIV : 0810.1261</identifier>
<relation>info:eu-repo/semantics/altIdentifier/arxiv/0810.1261</relation>
<language>en</language>
<subject lang=en>soft spectral clustering</subject>
<subject lang=en>clustering</subject>
<subject lang=en>text segmentation</subject>
<subject lang=en>language identification</subject>
<subject lang=en>multilingual corpora</subject>
<subject lang=en>markov chains</subject>
<subject>ACM H.3.3; I.2.7</subject>
<subject>[INFO.INFO-CL] Computer Science [cs]/Computation and Language [cs.CL]</subject>
<subject>[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]</subject>
<type>info:eu-repo/semantics/conferenceObject</type>
<type>Conference papers</type>
<description lang=en>Without prior knowledge, distinguishing different languages may be a hard task, especially when their borders are permeable. We develop an extension of spectral clustering -- a powerful unsupervised classification toolbox -- that is shown to resolve accurately the task of soft language distinction. At the heart of our approach, we replace the usual hard membership assignment of spectral clustering by a soft, probabilistic assignment, which also presents the advantage to bypass a well-known complexity bottleneck of the method. Furthermore, our approach relies on a novel, convenient construction of a Markov chain out of a corpus. Extensive experiments with a readily available system clearly display the potential of the method, which brings a visually appealing soft distinction of languages that may define altogether a whole corpus.</description>
<date>2006-08</date>
</dc>
</metadata>
</record>
</GetRecord>
</OAI-PMH>
