  With the digitization of travel industry, it is more and more important to
understand users from their online behaviors. However, online travel industry
data are more challenging to analyze due to extra sparseness, dispersed user
history actions, fast change of user interest and lack of direct or indirect
feedbacks. In this work, a new similarity method is proposed to measure the
destination similarity in terms of implicit user interest. By comparing the
proposed method to several other widely used similarity measures in recommender
systems, the proposed method achieves a significant improvement on travel data.
Key words: Destination similarity, Travel industry, Recommender System,
Implicit user interest
