A Personalized Trust-Aware Model for Travelogue Discovering

Nowadays, many social tourism platforms, such as tripadvisor.com and lvping.com, provide tourists opportunities to share their experiences on tourism destinations, services and sites. The increasing number of these available opinions makes potential travelers impossible easily discovering helpful information from an immense number of lengthy travelogues. Therefore, it is vitally important to develop models and algorithms to assist potential tourists access useful travelogues. This paper proposes a travelogue discovering model that incorporates the implicit trust relations among the social tourism platform, with the aim of discovering the most suitable travelogue for travelers. In addition, the model generates personalized assistance for tourists. The empirical study confirms the effectiveness of our proposed model in discovering helpful travelogues.