Treemap Representations of Higher Order Information for Moving Objects

被引：0
|
作者：
Wang, Ye [1 ]
Lee, Kyungmi [1 ]
Lee, Ickjai [1 ]
机构：
[1] James Cook Univ, Coll Business Law & Governance, Informat Technol Acad, POB 6811, Cairns, Qld 4870, Australia
来源：
2015 10TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS AND KNOWLEDGE ENGINEERING (ISKE) | 2015年
关键词：
Higher order information; spatio-temporal trajectory; higher order Voronoi diagrams; Treemap; VISUALIZATION; SPACE; TRAJECTORIES;
D O I：
10.1109/ISKE.2015.49
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Higher order Voronoi diagram is a popular way to model higher order information for complex decision making such as "what-if" analysis. Visualising higher order information for moving objects is a challenging task due to the marriage between higher order complexity and dynamic nature of moving objects. Treemap is a popular visualisation method to display hierarchical information as a set of nested rectangles, and it is a solid candidate for visualising higher order information. Previous researchers have got less attention to build up treemap with higher order information. This study presents a robust way to represent higher order information for moving objects through treemaps. We emphatically experiment well-studied 7 different treemap layouts for higher order information of moving objects, and evaluate their performance with two metric measures: aspect ratio and distance change.
引用
收藏
页码：287 / 294
页数：8
相关论文
共 50 条
  • [41] Design, Adaptation and Convention: The Emergence of Higher Order Graphical Representations
    Fay, Nicolas
    Garrod, Simon
    MacLeod, Tracy
    Lee, John
    Oberlander, Jon
    PROCEEDINGS OF THE TWENTY-SIXTH ANNUAL CONFERENCE OF THE COGNITIVE SCIENCE SOCIETY, 2004, : 363 - 368
  • [42] Graph Representations for Higher-Order Logic and Theorem Proving
    Paliwal, Aditya
    Loos, Sarah M.
    Rabe, Markus N.
    Bansal, Kshitij
    Szegedy, Christian
    THIRTY-FOURTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THE THIRTY-SECOND INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE AND THE TENTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2020, 34 : 2967 - 2974
  • [43] Higher order superintegrability, Painleve transcendents and representations of polynomial algebras
    Marquette, Ian
    32ND INTERNATIONAL COLLOQUIUM ON GROUP THEORETICAL METHODS IN PHYSICS (GROUP32), 2019, 1194
  • [44] Balanced state representations from higher-order models
    Willems, JC
    Rapisarda, P
    EQUADIFF 2003: INTERNATIONAL CONFERENCE ON DIFFERENTIAL EQUATIONS, 2005, : 587 - 592
  • [45] Higher order Borel-Pompeiu representations in Clifford analysis
    Bory Reyes, Juan
    De Schepper, Hennie
    Adan, Ali Guzman
    Sommen, Frank
    MATHEMATICAL METHODS IN THE APPLIED SCIENCES, 2016, 39 (16) : 4787 - 4796
  • [46] Higher-order Cayley transforms with applications to attitude representations
    Tsiotras, P
    Junkins, JL
    Schaub, H
    JOURNAL OF GUIDANCE CONTROL AND DYNAMICS, 1997, 20 (03) : 528 - 534
  • [47] Flatness and higher order differential model representations in dynamic optimization
    Oldenburg, J
    Marquardt, W
    COMPUTERS & CHEMICAL ENGINEERING, 2002, 26 (03) : 385 - 400
  • [48] Learning Network Representations With Different Order Structural Information
    Liu, Qidong
    Zhou, Xin
    Long, Cheng
    Zhang, Jie
    Xu, Mingliang
    IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS, 2020, 7 (04) : 907 - 914
  • [49] New higher order affine time-frequency representations
    Murray, RL
    Papandreou-Suppappola, A
    Boudreaux-Bartels, GF
    PROCEEDINGS OF THE IEEE-SP INTERNATIONAL SYMPOSIUM ON TIME-FREQUENCY AND TIME-SCALE ANALYSIS, 1998, : 325 - 328
  • [50] CORRECTNESS OF PROCEDURE REPRESENTATIONS IN HIGHER-ORDER ASSEMBLY LANGUAGE
    WAND, M
    LECTURE NOTES IN COMPUTER SCIENCE, 1992, 598 : 294 - 311
12345