A Knowledge Discovery Framework for Spatiotemporal Data Mining

被引:1
|
作者
Lee, Jun-Wook [1 ]
Lee, Yong-Joon [1 ]
机构
[1] ETRI, Telemat USN Res Div, Daejeon, South Korea
来源
关键词
spatiotemporal data mining; spatiotemporal knowledge discovery; spatiotemporal moving pattern; discovery framework;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the explosive increase in the generation and utilization of spatiotemporal data sets, many research efforts have been focused on the efficient handling of the large volume of spatiotemporal sets. With the remarkable growth of ubiquitous computing technology, mining from the huge volume of spatiotemporal data sets is regarded as a core technology which can provide real world applications with intelligence. In this paper, we propose a 3-tier knowledge discovery framework for spatiotemporal data mining. This framework provides a foundation model not only to define the problem of spatiotemporal knowledge discovery but also to represent new knowledge and its relationships. Using the proposed knowledge discovery framework, we can easily formalize spatiotemporal data mining problems. The representation model is very useful in modeling the basic elements and the relationships between the objects in spatiotemporal data sets, information and knowledge.
引用
收藏
页码:124 / 129
页数:6
相关论文
共 50 条
  • [1] A DESCRIPTIVE FRAMEWORK FOR THE FIELD OF DATA MINING AND KNOWLEDGE DISCOVERY
    Peng, Yi
    Kou, Gang
    Shi, Yong
    Chen, Zhengxin
    [J]. INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING, 2008, 7 (04) : 639 - 682
  • [2] A systemic framework for the field of data mining and knowledge discovery
    Peng, Yi
    Kou, Gang
    Shi, Yong
    Chen, Zhengxin
    [J]. ICDM 2006: SIXTH IEEE INTERNATIONAL CONFERENCE ON DATA MINING, WORKSHOPS, 2006, : 395 - 399
  • [3] A flexible framework for data mining and knowledge discovery in psychiatric genetics
    Moore, JH
    Gilbert, JC
    Barney, N
    Holden, W
    White, BC
    [J]. AMERICAN JOURNAL OF MEDICAL GENETICS PART B-NEUROPSYCHIATRIC GENETICS, 2005, 138B (01) : 6 - 6
  • [4] Data mining for knowledge discovery in mining
    Golosinski, TS
    Hu, H
    [J]. MINE PLANNING AND EQUIPMENT SELECTION 2001, 2001, : 1011 - 1018
  • [5] Knowledge discovery and data mining
    Lee, HY
    Lu, HJ
    Motoda, H
    [J]. KNOWLEDGE-BASED SYSTEMS, 1998, 10 (07) : 401 - 402
  • [6] Knowledge discovery and data mining
    Brodley, CE
    Lane, T
    Stough, TM
    [J]. AMERICAN SCIENTIST, 1999, 87 (01) : 54 - 61
  • [7] Data mining and knowledge discovery
    Trybula, WJ
    [J]. ANNUAL REVIEW OF INFORMATION SCIENCE AND TECHNOLOGY, 1997, 32 : 197 - 229
  • [8] An enterprise modeling and integration framework based on knowledge discovery and data mining
    Neaga, EI
    Harding, JA
    [J]. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2005, 43 (06) : 1089 - 1108
  • [9] A knowledge discovery framework for the assessment of tactical behaviour in soccer based on spatiotemporal data
    Hoch, T.
    Tan, X.
    Leser, R.
    Baca, A.
    Moser, B. A.
    [J]. MATHEMATICAL AND COMPUTER MODELLING OF DYNAMICAL SYSTEMS, 2017, 23 (04) : 384 - 398
  • [10] Data Mining and Knowledge Discovery Technologies
    Bacao, Fernando
    [J]. ONLINE INFORMATION REVIEW, 2008, 32 (06) : 866 - 867