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Incremental Clustering of Mobile Objects

Sigal Elnekave, Mark Last, Oded Maimon
2007 2007 IEEE 23rd International Conference on Data Engineering Workshop  
In this research we use a compact representation of a mobile trajectory and define a new similarity measure between trajectories.  ...  We also propose an incremental clustering algorithm for finding evolving groups of similar mobile objects in spatio-temporal data.  ...  trajectories of moving objects as 'moving clusters'.  ... 
doi:10.1109/icdew.2007.4401044 dblp:conf/icde/ElnekaveLM07 fatcat:uv2pesdkdfbqpdfokemkvpmc5i

Clustering Moving Object Trajectories: Integration in CROSS-CPP Analytic Toolbox

Alberto Blazquez-Herranz, Juan-Ignacio Caballero-Garzon, Albert Zilverberg, Christian Wolff, Alejandro Rodríguez-Gonzalez, Ernestina Menasalvas
2021 Applied Sciences  
Based on previous work on clustering algorithms we present in this paper a Quickbundels algorithm adaptation to trajectory clustering .  ...  As part of these analytic tools, a set of functionalities has been developed to cluster trajectories.  ...  In conclusion, in this paper, we have presented results of the integration of Quickbundles algorithm for the moving objects trajectories clustering in the CROSS-CPP platform.  ... 
doi:10.3390/app11083693 fatcat:b5vn72zjczez7d2ruwvbc67y2i

Discovering regular groups of mobile objects using incremental clustering

Sigal Elnekave, Mark Last, Oded Maimon, Yehuda Ben-Shimol, Hans Einsiedler, Menahem Friedman, Matthias Siebert
2008 2008 5th Workshop on Positioning, Navigation and Communication  
The proposed clustering algorithm uses a new, "data-amount-based" similarity measure between mobile trajectories.  ...  In order to discover groups of mobile objects that usually move in similar ways we propose an incremental clustering algorithm that clusters mobile objects according to similarity of their movement patterns  ...  [1] present a literature review on the subject of clustering.  ... 
doi:10.1109/wpnc.2008.4510375 dblp:conf/wpnc/ElnekaveLMBEFS08 fatcat:sfkjwou4mrbg7eheranqc22pra

Big Trajectory Data Mining: A Survey of Methods, Applications, and Services

Di Wang, Tomio Miwa, Takayuki Morikawa
2020 Sensors  
With a focus on relevance and association, our review is aimed at inspiring researchers to identify gaps among tested methods and guiding data analysts and planners to select the most suitable methods  ...  The increasingly wide usage of smart infrastructure and location-aware terminals has helped increase the availability of trajectory data with rich spatiotemporal information.  ...  Profiling of Moving Objects Starting from the trajectory, the most direct type of research would be to profile the moving object that generates the trajectory.  ... 
doi:10.3390/s20164571 pmid:32824028 pmcid:PMC7472055 fatcat:bgav5exs3nejhp42bbakf3ftp4

Clustering moving object trajectories: Integration in CROSS-CPP analytic toolbox

Alberto, Juan Ignacio, Albert, Christian, Alejandro, Ernestina
2021 Zenodo  
As part of these analytic tools, a set of functionalities have been developed to cluster trajectories.  ...  Based on previous work on clustering algorithms we present in this paper Quickbundels algorithm adaptation to trajectory clustering algorithm.  ...  A trajectory is the path followed by a moving object.  ... 
doi:10.5281/zenodo.4633091 fatcat:kop6pr6swvebhpzchv7yyvliru

AN INNOVATIVE IDEA TO DISCOVER THE TREND ON MULTI-DIMENSIONAL SPATIO-TEMPORAL DATASETS

N. Naga Saranya .
2014 International Journal of Research in Engineering and Technology  
Here it briefly describes the scope and relevancy of spatiotemporal data. From that, gain the depth knowledge of spatio-temporal recent research process to discover the trend.  ...  Here it briefly describes the scope and relevancy of spatio-temporal data. From the literature survey it has listed a number of issues.  ...  The proposed algorithms evaluation process of this research will be learned in our next research paper.  ... 
doi:10.15623/ijret.2014.0303046 fatcat:qoyuzflmbvfozgle4nmwkvl23q

Trajectory data mining: A review of methods and applications

Jean Damascène Mazimpaka, Sabine Timpf
2016 Journal of Spatial Information Science  
The increasing use of location-aware devices has led to an increasing availability of trajectory data.  ...  As a result, researchers devoted their efforts to developing analysis methods including different data mining methods for trajectories.  ...  They also would like to thank the anonymous reviewers for their comments that helped to improve the paper.  ... 
doi:10.5311/josis.2016.13.263 fatcat:cuxgsxpslfeunehzawbgctu4r4

A Novel Approach for Mining Trajectory Patterns of Moving Vehicles

Vaishali Mirge, Shubhrata Gupta, Keshri Verma
2014 International Journal of Computer Applications  
This paper proposes a novel algorithm to get trajectory patterns as a sequence of spatio-temporal regions. These sequences specify the paths heavily loaded with vehicles in certain duration.  ...  moving objects such as animals, vehicles, mobile devices, and climate radars have become widely available.  ...  Definition 1 (Trajectory) A trajectory is a trace generated by a moving object in geographical spaces, usually represented by a series of chronologically ordered points, {(x 0 ,y 0 ,t 0 ),...  ... 
doi:10.5120/18188-9097 fatcat:fkaqb2ej2vdx7m4othn5ierqse

Analyzing Trajectories Using Uncertainty and Background Information [chapter]

Bart Kuijpers, Bart Moelans, Walied Othman, Alejandro Vaisman
2009 Lecture Notes in Computer Science  
A key issue in clustering data, regardless the algorithm used, is the definition of a distance function.  ...  A well-known model to deal with uncertainty in a trajectory sample, uses the notion of space-time prisms (also called beads), to estimate the positions where the object could have been, given a maximum  ...  Clustering moving object trajectories requires, for example, finding out a proper spatial granularity level, and it is not obvious to identify the best clustering algorithm among the wide corpus of work  ... 
doi:10.1007/978-3-642-02982-0_11 fatcat:7yjvr5242nb75jwi5ixjoo5g6a

A system for learning statistical motion patterns

Weiming Hu, Xuejuan Xiao, Zhouyu Fu, D. Xie, Tieniu Tan, S. Maybank
2006 IEEE Transactions on Pattern Analysis and Machine Intelligence  
Each cluster centroid corresponds to a moving object or a part of a moving object.  ...  This algorithm is based on the principle that a moving object is always associated with a cluster of pixels in the feature space and the features of each cluster change only slightly between consecutive  ...  Now, he is a professor and a PhD student supervisor in the lab.  ... 
doi:10.1109/tpami.2006.176 pmid:16929731 fatcat:mg7b35qxtzenrnlmq273fkzd2y

A New Measurement Method to Calculate Similarity of Moving Object Spatio-Temporal Trajectories by Compact Representation

Zhao XiuLi, Xu WeiXiang
2011 International Journal of Computational Intelligence Systems  
A new measurement method is proposed to calculate spatio-temporal trajectory similarity, which can reflect the similar degree between two moving object spatio-temporal trajectories compressed by the Maximal  ...  And then, a similarity measurement formula is proposed by integrating these factors. Experiments show that the proposed measurement formula can improve the value of clustering index Dunn.  ...  Acknowledgments The authors gratefully acknowledge the editor and anonymous reviewers for their valuable comments and constructive suggestions.  ... 
doi:10.1080/18756891.2011.9727862 fatcat:pqff6mvysrcdthwxjkifmwt4ge

Discovery of Loose Group Companion from Trajectory Data Streams

Thi Thi Shein, Sutheera Puntheeranurak, Makoto Imamura
2020 IEEE Access  
Existing algorithms, studying the evolving structure of moving object trajectories, have high computational complexity, particularly when tracking loose group companions.  ...  INDEX TERMS Group pattern, loose group companion, trajectory data stream, moving object clustering, spatial-temporal pattern. 85856 This work is licensed under a Creative Commons Attribution 4.0 License  ...  RELATED WORK We review previous works on trajectory data clustering and various kinds of moving object group pattern discovery from trajectory data. A.  ... 
doi:10.1109/access.2020.2992596 fatcat:vcgfaqdou5e25e4z6245k7n2tq

Massively Parallel Discovery of Loosely Moving Congestion Patterns from Trajectory Data

Chunchun Hu, Si Chen
2021 ISPRS International Journal of Geo-Information  
In this study, we propose the concept of loosely moving congestion patterns that represent a group of moving objects together with similar movement tendency and loose coherence moving, which exhibit a  ...  The efficient discovery of significant group patterns from large-scale spatiotemporal trajectory data is a primary challenge, particularly in the context of urban traffic management.  ...  First, we review the related work on the spatiotemporal trajectory data analysis of moving objects.  ... 
doi:10.3390/ijgi10110787 fatcat:tjcmzjcnu5entauygxgx5v5ypy

Developing a Spatial-Temporal Contextual and Semantic Trajectory Clustering Framework [article]

Ivens Portugal, Paulo Alencar, Donald Cowan
2017 arXiv   pre-print
between the dimensions of a pair of trajectories; and (iii) big data approaches that can be used to develop a novel spatial-temporal clustering framework.  ...  Trajectory analysis methods based on clustering techniques heavily often rely on a similarity definition to properly provide insights.  ...  A trajectory is, in simple terms, the sequence of positions that a moving spatial-temporal object has taken during a specific time [15] .  ... 
arXiv:1712.03900v1 fatcat:ezz7gy5w6bafvdvp4fjvcut6te

Design of intelligent acquisition system for moving object trajectory data under cloud computing

Yang Zhang, Abhinav Asthana, Sudeep Asthana, Shaweta Khanna, Ioan-Cosmin Mihai
2021 Journal of Intelligent Systems  
In order to study the intelligent collection system of moving object trajectory data under cloud computing, information useful to passengers and taxi drivers is collected from massive trajectory data.  ...  This paper uses cloud computing technology, through clustering algorithm and density-based DBSCAN algorithm combined with Map Reduce programming model and design trajectory clustering algorithm.  ...  Literature reviews of various techniques and algorithms are detailed in Section 2. Section 3 discusses the system design and parallel design of trajectory clustering algorithm.  ... 
doi:10.1515/jisys-2020-0152 fatcat:ugpxtv5icjbtdooyoyot5sax2q
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