Travel Review Analysis System with Big Data (TRAS)

摘要

This paper introduces a process for online travel review analysis in Thai language employed in a recommender system supporting travelers (TRAS). The process covers three main categories: attractions, accommodation, and gastronomy. The filtering and queuing results gained with MapReduce build the input for three main steps: (1) the analysis process for element scores, (2) the analysis process for the total scores of the reviews, and (3) the travel guidance system based on users' selections. The extensive tests revealed that the system operates properly regarding functional and non-functional requirements. We employed 60,000 travel reviews containing all categories to test the analysis process for steps (1) and (2). We found that the number of adjectives and modifiers in each review affects the time used for analysis. In contrast to previous recommender systems, TRAS applies a more diverse and transparent rating and ranking approach. Travelers can select the features they are interested in and get personalized results, so that a given location might achieve different rankings for different travelers.