English   español  
Por favor, use este identificador para citar o enlazar a este item: http://hdl.handle.net/10261/155823
COMPARTIR / IMPACTO:
Estadísticas
logo share SHARE logo core CORE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar a otros formatos:
Título

Concept Discovery and Argument Bundles in the Experience Web

AutorFerrer, Xavier ; Plaza, Enric
Palabras claveSentiment analysis
Experience web
Basic level concepts
Aspect extraction
Arguments
Fecha de publicación31-oct-2016
EditorSpringer
Citación 24th International Conference on Case-Based Reasoning Research and Development, ICCBR 2016; LNAI 9969 (2016): 108-123.
ResumenIn this paper we focus on a particular interesting web user-generated content: people¿s experiences. We extend our previous work on aspect extraction and sentiment analysis and propose a novel approach to create a vocabulary of basic level concepts with the appropriate granularity to characterize a set of products. This concept vocabulary is created by analyzing the usage of the aspects over a set of reviews, and allows us to find those features with a clear positive and negative polarity to create the bundles of arguments. The argument bundles allow us to define a concept-wise satisfaction degree of a user query over a set of bundles using the notion of fuzzy implication, allowing the reuse experiences of other people to the needs a specific user. © Springer International Publishing AG 2016.
URIhttp://hdl.handle.net/10261/155823
DOI10.1007/978-3-319-47096-2_8
Identificadoresdoi: 10.1007/978-3-319-47096-2_8
issn: 03029743
isbn: 978-331947095-5
Aparece en las colecciones: (IIIA) Comunicaciones congresos
Ficheros en este ítem:
Fichero Descripción Tamaño Formato  
LNAI9969_108-123.pdf719,22 kBAdobe PDFVista previa
Visualizar/Abrir
Mostrar el registro completo
 


NOTA: Los ítems de Digital.CSIC están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.