INFORMATION TECHNOLOGY FOR TRAJECTORY DATA MINING

被引:0
作者
Sydorova, M. [1 ]
Baybuz, O. [1 ]
Verba, O. [1 ]
Pidhornyi, P. [1 ]
机构
[1] Oles Honchar Dnipro Natl Univ, 72 Gagarin Ave, UA-49010 Dnipro, Ukraine
来源
SCIENCE AND INNOVATION | 2021年 / 17卷 / 03期
关键词
information technology; pattern mining; trajectory of motion; points and sequences of interest; clus-ter analysis; similarity measure;
D O I
10.15407/scine17.03.078
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Introduction. Advanced technologies allow almost continuous tracking and recording the movement of objects in space and time. Detecting interesting patterns in these data, popular routes, habits, and anomalies in object motion and understanding mobility behaviors are actual tasks in different application areas such as marketing, urban planning, transportation, biology, ecology, etc. Problem Statement. In order to obtain useful information from trajectories of moving objects, it is important to develop and to improve mathematical methods of spatiotemporal analysis and to implement them in high quality modern software. Purpose. The purpose of this research is the development of information technology for trajectory data mining. Materials and Methods. Information technology contains the three main algorithms: revealing key points and sequences of interest with the use of density-based trajectories clustering of studied objects; detecting patterns of an object movement based on association rules and hierarchical cluster analysis of its motion trajectories in the time interval of observations, similarity measure of the motion trajectories has been proposed to be calculated on the basis of the DTW method with the use of the modified Haversine formula; new algorithm for revealing permanent routes and detecting groups of similar objects has been developed on the basis of clustering ensembles of all studied trajectories in time. The clustering parameters are selected with multi-criteria quality evaluation. Results. The modern software that implements the proposed algorithms and provides a convenient interaction with users and a variety of visualization tools has been created. The developed algorithms and software have been tested in detail on the artificial trajectories of moving objects and applied to analysis of real open databases. Conclusions. The experiments have confirmed the efficiency of the proposed information technology that may have a practicable application to trajectory data mining in various fields.
引用
收藏
页码:78 / 86
页数:9
相关论文
共 13 条
  • [1] Andrienko N, 2006, Exploratory Analysis of Spatial and Temporal Data - A Systematic Approach
  • [2] Spatio-Temporal Data Mining: A Survey of Problems and Methods
    Atluri, Gowtham
    Karpatne, Anuj
    Kumar, Vipin
    [J]. ACM COMPUTING SURVEYS, 2018, 51 (04)
  • [3] Baibuz O. G., 2014, NAUKOVYI VISNYK NATS, V2014, P11
  • [4] Cai L., 2018, ANN DATA SCI, V5, P43, DOI [https://doi.org/10.1007/s40745-017-0132-1, DOI 10.1007/S40745-017-0132-1]
  • [5] Cartographic visualisation of human trajectory data: overview and analysis
    Goncalves, Tiago
    Afonso, Ana Paula
    Martins, Bruno
    [J]. JOURNAL OF LOCATION BASED SERVICES, 2015, 9 (02) : 138 - 166
  • [6] Dynamic Recommendation of POI Sequence Responding to Historical Trajectory
    Huang, Jianfeng
    Liu, Yuefeng
    Chen, Yue
    Jia, Chen
    [J]. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2019, 8 (10)
  • [7] Trajectory data mining: A review of methods and applications
    Mazimpaka, Jean Damascene
    Timpf, Sabine
    [J]. JOURNAL OF SPATIAL INFORMATION SCIENCE, 2016, (13): : 61 - 99
  • [8] Rao KV., 2012, INT J COMPUT SCI ENG, V3, P39, DOI [10.5121/ijcses.2012.3104, DOI 10.5121/IJCSES.2012.3104]
  • [9] Sidorova M., 2012, 2012 11th International Conference on "Modern Problems of Radio Engineering, Telecommunications and Computer Science"
  • [10] Sidorova M, 2018, 2018 14TH INTERNATIONAL CONFERENCE ON ADVANCED TRENDS IN RADIOELECTRONICS, TELECOMMUNICATIONS AND COMPUTER ENGINEERING (TCSET), P958, DOI 10.1109/TCSET.2018.8336352