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dc.date.accessioned 2012-10-17T14:23:55Z
dc.date.available 2012-10-17T14:23:55Z
dc.date.issued 2004
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/22561
dc.description.abstract The volume of documents available electronically is growing fast, so it becomes difficult to access and select desired information in a fast and efficient way. In this context the automatic summarization task assumes a very imperative role; therefore one seeks to reduce the size of a document, preserving to the maximum its informative content. In this paper, it’s applied a model which uses sentence clusters from an ART2 neural network to generate extractive summaries. Different models can be developed from distinct area documents. Hence, the aim of this work is to evaluate the performance of those models when they summarize documents from correlated or non correlated areas. en
dc.language en es
dc.subject ART2 en
dc.subject Neural nets es
dc.subject ARTIFICIAL INTELLIGENCE es
dc.subject Create Summaries en
dc.subject Texts of Different Areas en
dc.subject Intelligent agents es
dc.title The Use of ART2 to create summaries from texts of different areas en
dc.type Objeto de conferencia es
sedici.creator.person Christ, Rafael E. R. es
sedici.creator.person Bassani, T. es
sedici.creator.person Nievola, Julio César es
sedici.creator.person Junior, Carlos N. Silla es
sedici.description.note Eje: V - Workshop de agentes y sistemas inteligentes es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Red de Universidades con Carreras en Informática (RedUNCI) es
sedici.subtype Objeto de conferencia es
sedici.rights.license Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
sedici.rights.uri http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
sedici.date.exposure 2004-10
sedici.relation.event X Congreso Argentino de Ciencias de la Computación es
sedici.description.peerReview peer-review es


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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) Except where otherwise noted, this item's license is described as Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)