An Information Retrieval System on Thailand Tourism Community Websites

Nowadays, there are many sharing travel knowledge on the internet such as community web-boards which allows most people prefer to post their travel experience. There are many content that implicated in the hotel, the restaurant, or even the travel route. Because of the Internet includes many review articles that makes the tourists spend a lot of time reading and summarizing articles. This research proposed the information retrieval model to search related articles to user needs. Moreover, the system tries to summarize the content related to tourism in the post to continue to know. In this research, we use vector space model to represent the keywords that are the social media content and applies the cosine similarity to indicate the ranking of related articles. The results are travel review article to guide the attractions, accommodations and location that help to plan the user's travel. The experiment results show that our tourism web-boards retrieval provides relevant information on high performance.