@Article{MonteiroSantFerr:2020:MiPaTr,
               author = "Monteiro, Diego Vilela and Santos, Rafael Duarte Coelho dos and 
                         Ferreira, Karine Reis",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "Mining partners in trajectories",
              journal = "International Journal of Data Warehousing and Mining",
                 year = "2020",
               volume = "16",
               number = "1",
                pages = "22--38",
                month = "jan./mar.",
             keywords = "Data Mining, Moving Objects, Pattern, R, Trajectory.",
             abstract = "Spatiotemporal data is everywhere, being gathered from different 
                         devices such as Earth Observation and GPS satellites, sensor 
                         networks and mobile gadgets. Spatiotemporal data collected from 
                         moving objects is of particular interest for a broad range of 
                         applications. In the last years, such applications have motivated 
                         many pieces of research on moving object trajectory data mining. 
                         In this article, it is proposed an efficient method to discover 
                         partners in moving object trajectories. Such a method identifies 
                         pairs of trajectories whose objects stay together during certain 
                         periods, based on distance time series analysis. It presents two 
                         case studies using the proposed algorithm. This article also 
                         describes an R package, called TrajDataMining, that contains 
                         algorithms for trajectory data preparation, such as filtering, 
                         compressing and clustering, as well as the proposed method 
                         Partner.",
                  doi = "10.4018/IJDWM.2020010102",
                  url = "http://dx.doi.org/10.4018/IJDWM.2020010102",
                 issn = "1548-3924",
             language = "en",
           targetfile = "monteiro_data.pdf",
        urlaccessdate = "28 abr. 2024"
}