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The rapid growth of internet based ride-sharing brings great changes to residents' travel and city traffic. However, few studies had employed empirical data to examine the unique travel patterns of internet based ride-sharing trips. In this paper, we compare taxi trip records and internet based ride-sharing trip records provided by DiDi company. Results reveal many interesting findings that had never been reported before. From the viewpoint of service patterns, ride-sharing mainly increases supplies in hot areas and peak hours. By applying a non-negative matrix factorization method, we find that ride-sharing principally serves as an approach for commuting. So, as an effective supplement to traditional taxi service, it regulates spatial and temporal supply-demand imbalance, especially during morning and evening rush periods. From the viewpoint of individual behavior patterns, we use a clustering method to identify …