Touristes and traveler use avariety of information sources (e.g. travelportals, blogs, or social networking sites like twitter) to help them decide for a hotel room. These sources all contain highly subjective text that expresses the opinions of many. We took a preliminary view on user generated hotel reviews from two travel portals in English and Thai. We developed a taxonomy of features and specifically investigated how accurately they can be predicted with three classification methods. The results indicate that support vector machines perform best for this specific domain.
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