The neural-semantic network: a new structure to representing conceptual knowledge and to support dynamically learning

被引：0
|
作者：
Qin Zhong-bao [1 ]
Wang You-jun [1 ]
Zhao Feng [1 ]
He Wei-ping [1 ]
机构：
[1] Xian Inst High Technol, Xian 710025, Peoples R China
来源：
ISTM/2007: 7TH INTERNATIONAL SYMPOSIUM ON TEST AND MEASUREMENT, VOLS 1-7, CONFERENCE PROCEEDINGS | 2007年
关键词：
spreading action model; neural-semantic cell; neural-semantic network; semantic association;
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：
This paper suggested a structure Of neural-semantic cell, which combined the explicitness of semantic network with the dynamic of artificial neural network together Moreover, based on the neural-semantic cell, a neutral-semantic network was constructed. the network cannot only represent explicitly the semantic information of the concepts, but also image dynamically the relationship between. concepts. By its leaning mechanism, the neural-semantic network can; enrich its conceptual knowledge and the semantic information of cells.
引用
收藏
页码：2684 / 2687
页数：4
相关论文
共 50 条
  • [31] A Learning Agent for Knowledge Extraction from an Active Semantic Network
    Thiel, Simon
    Dalakakis, Stavros
    Roller, Dieter
    PROCEEDINGS OF WORLD ACADEMY OF SCIENCE, ENGINEERING AND TECHNOLOGY, VOL 7, 2005, 7 : 217 - 220
  • [32] A learning agent for knowledge extraction from an active semantic network
    Thiel, S
    Dalakakis, S
    Roller, D
    ENFORMATIKA, VOL 7: IEC 2005 PROCEEDINGS, 2005, : 217 - 220
  • [33] SLNN: A neural network for fuzzy neural network's structure learning
    Tian, Daxin
    Liu, Yanheng
    Wang, Jian
    ISDA 2006: SIXTH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS, VOL 1, 2006, : 919 - 924
  • [34] Uncovering Semantic Bias in Neural Network Models Using a Knowledge Graph
    Nikolov, Andriy
    d'Aquin, Mathieu
    CIKM '20: PROCEEDINGS OF THE 29TH ACM INTERNATIONAL CONFERENCE ON INFORMATION & KNOWLEDGE MANAGEMENT, 2020, : 1175 - 1184
  • [35] Learning semantic program embeddings with graph interval neural network
    Wang, Yu
    Wang, Ke
    Gao, Fengjuan
    Wang, Linzhang
    1600, Association for Computing Machinery (04):
  • [36] Learning Semantic Program Embeddings with Graph Interval Neural Network
    Wang, Yu
    Wang, Ke
    Gao, Fengjuan
    Wang, Linzhang
    PROCEEDINGS OF THE ACM ON PROGRAMMING LANGUAGES-PACMPL, 2020, 4
  • [37] Knowledge-based neural network: A method to support learners in building neural network models
    Okamoto, T
    Belkada, S
    KNOWLEDGE-BASED SOFTWARE ENGINEERING, 2000, 62 : 315 - 322
  • [38] Learning by Conceptual Modeling-Changes in Knowledge Structure and Content
    Zitek, Andreas
    Poppe, Michaela
    Stelzhammer, Michael
    Muhar, Susanne
    Bredeweg, Bert
    IEEE TRANSACTIONS ON LEARNING TECHNOLOGIES, 2013, 6 (03): : 217 - 227
  • [39] A new dynamically convergent differential neural network for brain signal recognition
    Zhang, Zhijun
    Sun, Jiansheng
    Chen, Tao
    BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2022, 71
  • [40] Hybrid Neural Network for Recognition of the "de" Structure with Semantic Ellipsis
    Shi B.
    Dai R.
    Qu W.
    Gu Y.
    Zhou J.
    Li B.
    Xu G.
    Shi S.
    Beijing Daxue Xuebao (Ziran Kexue Ban)/Acta Scientiarum Naturalium Universitatis Pekinensis, 2019, 55 (01): : 75 - 83
12345