A lexiconizing framework of feature-based opinion mining in tourism industry

Abstract

Among of the travel agency business in Thailand, Agoda (www.agoda.com) has boomed in recent years with the number of online agents offering for hotels booking. When customers need to make decision, they typically explore by investigating the opinions attached with each hotel in online agent. This paper proposes a framework of feature-based opinion mining by using scores which essentially relies on the usage of two main lexiconizing levels, features and polar words. An approach for extracting features and polar words from textual opinion is based on syntactic pattern analysis. The evaluation is performed with existing opinions and compared the statistical resulted scores with the existing scores of each hotel. The proposed scoring method is proven for the effectiveness of the score from Agoda and could facilitate the further text retrieval application development for the benefit of automatic customer's opinion detection. © 2014 IEEE.