Concept Discovery and Argument Bundles in the Experience Web
In 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...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2016 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/155823 |
| Acceso en línea: | http://hdl.handle.net/10261/155823 |
| Access Level: | acceso abierto |
| Palabra clave: | Sentiment analysis Experience web Basic level concepts Aspect extraction Arguments |
| Sumario: | In 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. |
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