Research on Patterns Mining Method for Moving Objects

Abstract

Abstract. Advanced technology in GPS and sensors enables us to track moving objects, such as human beings, animals, vehicles. These mobility data as historical activity data of moving objects, in some degree can reflect some internal and external features of moving objects, how to use the massive high-precision mobile data identify potential and meaningful pattern is the current hot spots and is also a serious problem. Patterns mining also have numerous applications in human mobility understanding, urban planning and ecological studies and a wide variety of other fields. In this paper, we provide a general perspective for studies on the issues of patterns mining by reviewing the methods and algorithms in detail and comparing the existing results on the same issues, providing a quick understanding of research to the worker.

Detecting behavior types of moving object trajectories

“…Authors in [25] provided a survey that discusses recent results on mining mobility patterns from GPS data. In [7], the authors give a general view for recent publications that discuss trajectory analysis methods and patterns mining issues, by reviewing the methods and algorithms recently used in this field in detail and comparing their different approaches. From literature, trajectory analysis methods can be summarized as clustering method, which concern to find a group of trajectories that share common sub-traces to measure the closeness using distance measures between trajectories, then use density-based clustering methods in order to cluster the trajectories [20,19].…”

Extracting Interesting Regions and Trips from Taxi Trajectory Data

“…According to (Chen et al, 2016), trajectory pattern mining methods are based on either clustering or frequency analysis of trajectories. Regardless of the method used, measuring the similarity between different trajectories is an important requirement for both methods.…”

“…These trajectories store important information regarding the navigation or the movement pattern of a fleet of people, vehicles, robots, animals, users of social networks, etc. Many research initiatives have applied data mining techniques in order to extract useful knowledge from trajectory data, which is recognised as trajectory data mining (Chen et al, 2016;Zheng, 2015;Lin and Hsu, 2014;Jeung et al, 2011;Giannotti et al, 2007). Various stakeholders are interested in mining the movement of different types of objects, including humans, in order to extract useful information, and hence, knowledge for many different reasons.…”