Detecting Commuting Patterns by Clustering Subtrajectories
نویسندگان
چکیده
In this paper we consider the problem of detecting commuting patterns in a trajectory. For this we search for similar subtrajectories. To measure spatial similarity we choose the Fréchet distance and the discrete Fréchet distance between subtrajectories, which are invariant under differences in speed. We give several approximation algorithms, and also show that the problem of finding the ‘longest’ subtrajectory cluster is as hard as MaxClique to compute and approximate.
منابع مشابه
Detecting Overlapping Communities in Social Networks using Deep Learning
In network analysis, a community is typically considered of as a group of nodes with a great density of edges among themselves and a low density of edges relative to other network parts. Detecting a community structure is important in any network analysis task, especially for revealing patterns between specified nodes. There is a variety of approaches presented in the literature for overlapping...
متن کاملAn Optimization K-Modes Clustering Algorithm with Elephant Herding Optimization Algorithm for Crime Clustering
The detection and prevention of crime, in the past few decades, required several years of research and analysis. However, today, thanks to smart systems based on data mining techniques, it is possible to detect and prevent crime in a considerably less time. Classification and clustering-based smart techniques can classify and cluster the crime-related samples. The most important factor in the c...
متن کاملSegmented trajectory based indexing and retrieval of video data
In this paper, we present a novel principal component analysis (PCA) based approach towards modeling the object trajectory in a video clip. An eigenspace decomposition of highdimensional trajectory data leads to very compact representation, which is then used as indexing structure. To cutback on PCA computation during indexing, we first segment the trajectories into atomic subtrajectories using...
متن کاملDetecting daily commuting distance from GPS trajectory
Most people have certain acceptance of daily travel distance, which determines where they choose to live, to work, and to go for leisure. Such information is an important input for facility location-allocation, urban planning and transport management. Therefore, daily commuting distance has been adopted as an indicator to measure the distance acceptance, the rationality of land use structure, a...
متن کاملDividing and Clustering Algorithms of Moving Objects in Rfid Tracing System
Trajectory clustering can predict moving trend of objects effectively. The traditional trajectory clustering algorithms take moving trajectory of a whole object as a research object, which will lose similar subtrajectories. However, in practical applications, such as in RFID system, the users may only focus on some specific regions of trajectories. We propose PT-CLUS algorithms in this paper, a...
متن کامل