Large-Scale Ontology Development and Agricultural Application Based on Knowledge Domain Framework

被引:4
|
作者
Meng Xian-xue [1 ]
Li Jing [2 ]
Su Xiao-lu [1 ,3 ]
Ku Hai-yan [1 ]
Wang Yi-qian [1 ]
机构
[1] Chinese Acad Agr Sci, Inst Agr Informat, Beijing 100081, Peoples R China
[2] China Natl Inst Standardizat, Natl Lib Stand, Beijing 100088, Peoples R China
[3] Minist Agr, Key Lab Agriinformat Serv Technol, Beijing 100081, Peoples R China
关键词
massive knowledge management; knowledge domain framework (KDF); large-scale ontology development environment (LODE); agricultural application;
D O I
10.1016/S2095-3119(12)60071-9
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
The key activity to build semantic web is to build ontologies. But today, the theory and methodology of ontology construction is still far from ready. This paper proposed a theoretical framework for massive knowledge management - the knowledge domain framework (KDF), and introduces an integrated development environment (IDE) named large-scale ontology development environment (LODE), which implements the proposed theoretical framework. We also compared LODE with other popular ontology development environments in this paper. The practice of using LODE on management and development of agriculture ontologies shows that knowledge domain framework can handle the development activities of large scale ontologies. Application studies based on the principle of knowledge domain framework and LODE was described briefly.
引用
收藏
页码:808 / 822
页数:15
相关论文
共 50 条
  • [21] A review of the large-scale application of autonomous mobility of agricultural platform
    Ren, Xu
    Huang, Bo
    Yin, Hesheng
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2023, 206
  • [22] A MultikeyRank Model Based on Ontology for Large-Scale Semantic Data
    Jiang Yang
    Feng Zhiyong
    Wang Xin
    CHINESE JOURNAL OF ELECTRONICS, 2014, 23 (01) : 119 - 123
  • [23] A segment-based approach for large-scale ontology matching
    Xingsi Xue
    Jeng-Shyang Pan
    Knowledge and Information Systems, 2017, 52 : 467 - 484
  • [24] A Clustering-Based Approach for Large-Scale Ontology Matching
    Algergawy, Alsayed
    Massmann, Sabine
    Rahm, Erhard
    ADVANCES IN DATABASES AND INFORMATION SYSTEMS, 2011, 6909 : 415 - 428
  • [25] Development and Application of Large-Scale Shaft Kilns
    Lang, Guanghui
    Liu, Rui
    Jiang, Yujing
    Li, Yan
    Logan, Ronald Lee
    LIGHT METALS 2018, 2018, : 1297 - 1302
  • [26] A segment-based approach for large-scale ontology matching
    Xue, Xingsi
    Pan, Jeng-Shyang
    KNOWLEDGE AND INFORMATION SYSTEMS, 2017, 52 (02) : 467 - 484
  • [27] Incorporating domain knowledge into data mining process: An ontology based framework
    Pan, Ding
    Shen, Jun-Yi
    Zhou, Mu-Xin
    Wuhan University Journal of Natural Sciences, 2006, 11 (01) : 165 - 169
  • [28] Incorporating Domain Knowledge into Data Mining Process:An Ontology Based Framework
    PAN Ding~ 1
    2. Department of Computer Science and Engineering
    WuhanUniversityJournalofNaturalSciences, 2006, (01) : 165 - 169
  • [29] A Platform based Distributed Service Framework for Large-scale Cloud Ecosystem Development
    Hu, Bo
    Wang, Jian
    Zhang, Liang-Jie
    Chen, Huan
    Luo, Lihui
    2015 IEEE WORLD CONGRESS ON SERVICES, 2015, : 87 - 94
  • [30] Supporting Ontology Design through Large-Scale FCA-Based Ontology Restructuring
    Rouane-Hacene, Mohamed
    Valtchev, Petko
    Nkambou, Roger
    CONCEPTUAL STRUCTURES FOR DISCOVERING KNOWLEDGE, 2011, 6828 : 257 - 269