Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
Communications of the ACM
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Propagation of trust and distrust
Proceedings of the 13th international conference on World Wide Web
Equip tourists with knowledge mined from travelogues
Proceedings of the 19th international conference on World wide web
On theme location discovery for travelogue services
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
How random walks can help tourism
ECIR'12 Proceedings of the 34th European conference on Advances in Information Retrieval
| Hi-index | 0.00 |
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.