Classification Rules to identify Context and Preference Information from Tourist’s Reviews
In many tourist sites have been incorporate box to allow people interchange experience, written comments and valuation about products or services. Many of the tourists planning decision are based on third-party opinions. Text mining is the discipline that extracts information from written text by u...
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| Formato: | Objeto de conferencia |
| Lenguaje: | Inglés |
| Publicado: |
2010
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| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/152655 http://39jaiio.sadio.org.ar/sites/default/files/39jaiio-asai-13.pdf |
| Aporte de: |
| Sumario: | In many tourist sites have been incorporate box to allow people interchange experience, written comments and valuation about products or services. Many of the tourists planning decision are based on third-party opinions. Text mining is the discipline that extracts information from written text by users/consumers in natural language to be understood by a computer system. In this paper is presented a text mining process to obtain classification rules in order to identify context information and consumer’s preferences from a review. User’s preferences are different according with a situation or context in which the review was expressed. This approach was exemplified by a case study using reviews from www.tripadvisor.com. |
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