Multi-entity Bayesian Networks for Treasuring the Intangible Cultural Heritage

被引:0
|
作者
Chantas, Giannis [1 ]
Nikolopoulos, Spiros [1 ]
Kompatsiaris, Ioannis [1 ]
机构
[1] Ctr Res & Technol Hellas, Informat Technol Inst, Thessaloniki, Greece
关键词
First-Order Logic; Multi-entity Bayesian Networks; Knowledge Modeling; Intangible Cultural Heritage;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we propose the use of Multi-entity Bayesian networks (MEBNs) for modeling the knowledge and analyzing the content pertaining to the domain of Intangible Cultural Heritage (ICH). MEBNs provide a rigorous knowledge representation framework in conjunction with reasoning and probabilistic inference capabilities. There are mainly two reasons motivating the use of MEBNs in the domain of ICH. The first is that MEBNs extend first-order logic with the ability to model uncertainty. The second reason is the capability of MEBN to adapt to specific situations by providing custom, situation specific Bayesian networks. Finally, we use an example to demonstrate the potential efficiency of MEBNs in the domain of ICH.
引用
收藏
页码:796 / 802
页数:7
相关论文
共 50 条
  • [1] Multi-entity Bayesian Networks for situation assessment
    Wright, E
    Mahoney, S
    Laskey, K
    Takikawa, M
    Levitt, T
    PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON INFORMATION FUSION, VOL II, 2002, : 804 - 811
  • [2] Multi-Entity Bayesian Networks Learning For Hybrid Variables In Situation Awareness
    Park, Cheol Young
    Laskey, Kathryn Blackmond
    Costa, Paulo C. G.
    Matsumoto, Shou
    2013 16TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION), 2013, : 1894 - 1901
  • [3] Data-organization before learning Multi-Entity Bayesian Networks structure
    Bouhamed, H.
    Rebai, A.
    Lecroq, T.
    Jaoua, M.
    World Academy of Science, Engineering and Technology, 2011, 78 : 305 - 308
  • [4] Multi-Entity Bayesian Networks for Knowledge-Driven Analysis of ICH Content
    Chantas, Giannis
    Kitsikidis, Alexandros
    Nikolopoulos, Spiros
    Dimitropoulos, Kosmas
    Douka, Stella
    Kompatsiaris, Ioannis
    Grammalidis, Nikos
    COMPUTER VISION - ECCV 2014 WORKSHOPS, PT II, 2015, 8926 : 355 - 369
  • [5] Game Theoretic Fuzzy Multi-Entity Bayesian Networks for Collision Avoidance in VANETs
    Golestan, Keyvan
    Soua, Ridha
    Karray, Fakhri
    Kamel, Mohamed S.
    2016 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE), 2016, : 508 - 515
  • [6] Predictive Situation Awareness Reference Model using Multi-Entity Bayesian Networks
    Park, Cheol Young
    Laskey, Kathryn Blackmond
    Costa, Paulo C. G.
    Matsumoto, Shou
    2014 17TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION), 2014,
  • [7] Situation Assessment Based on Multi-Entity Bayesian Network
    Shi, Guoqing
    Pu, Junwei
    Zhang, Lin
    Geng, Xiutang
    Zhou, Yu
    Zhao, Yahang
    2020 IEEE 16TH INTERNATIONAL CONFERENCE ON CONTROL & AUTOMATION (ICCA), 2020, : 702 - 707
  • [8] Multi-entity Bayesian network for the handling of uncertainties in SATCOM Links
    Tian, Xin
    Chen, Genshe
    Martin, Todd
    Chang, K. C.
    Tien Nguyen
    Khanh Pham
    Blasch, Erik
    SENSORS AND SYSTEMS FOR SPACE APPLICATIONS VIII, 2015, 9469
  • [9] Aerial Target Recognition Based on Multi-entity Bayesian Network
    Zhang, Jiandong
    Feng, Zhanbo
    Shi, Guoqing
    Liu, Yunzhou
    Li, Xuewei
    2022 IEEE 17TH INTERNATIONAL CONFERENCE ON CONTROL & AUTOMATION, ICCA, 2022, : 261 - 266
  • [10] A Process for Human-aided Multi-Entity Bayesian Networks Learning in Predictive Situation Awareness
    Park, Cheol Young
    Laskey, Kathryn Blackmond
    Costa, Paulo C. G.
    Matsumoto, Shou
    2016 19TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION), 2016, : 2116 - 2124