Busque entre los 155995 recursos disponibles en el repositorio
Mostrar el registro sencillo del ítem
dc.date.accessioned | 2013-11-21T14:21:02Z | |
dc.date.available | 2013-11-21T14:21:02Z | |
dc.date.issued | 2013-10 | |
dc.identifier.uri | http://sedici.unlp.edu.ar/handle/10915/31256 | |
dc.description.abstract | Obtaining the most representative set of words in a document is a very significant task, since it allows characterizing the document and simplifies search and classification activities. This paper presents a novel method, called LIKE, that offers the ability of automatically extracting keywords from a document regardless of the language used in it. To do so, it uses a three-stage process: the first stage identifies the most representative terms, the second stage builds a numeric representation that is appropriate for those terms, and the third one uses a feed-forward neural network to obtain a predictive model. To measure the efficacy of the LIKE method, the articles published by the Workshop of Computer Science Researchers (WICC) in the last 14 years (1999-2012) were used. The results obtained show that LIKE is better than the KEA method, which is one of the most widely mentioned solutions in literature about this topic. | en |
dc.language | es | es |
dc.subject | Data mining | es |
dc.subject | text mining | en |
dc.subject | DATABASE MANAGEMENT | es |
dc.subject | document characterization | en |
dc.subject | back-propagation | en |
dc.title | A novel, Language-Independent Keyword Extraction method | en |
dc.type | Objeto de conferencia | es |
sedici.creator.person | Aquino, Germán Osvaldo | es |
sedici.creator.person | Hasperué, Waldo | es |
sedici.creator.person | Estrebou, César Armando | es |
sedici.creator.person | Lanzarini, Laura Cristina | es |
sedici.description.note | X Workshop bases de datos y minería de datos | 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.relation.event | XVIII Congreso Argentino de Ciencias de la Computación | es |
sedici.description.peerReview | peer-review | es |