Semantic interoperability of large systems through a formal method: Relational Concept Analysis

被引:5
|
作者
Wajnberg, Mickael [1 ,2 ]
Lezoche, Mario [2 ]
Blondin-Masse, Alexandre [1 ]
Valchev, Petko [1 ]
Panetto, Herve [2 ]
Tyvaert, Louise [2 ]
机构
[1] Univ Quebec Montreal, Dept Informat, CP 8888, Montreal, PQ H3C 3P8, Canada
[2] Univ Lorraine, CNRS, Res Ctr Automat Control, CRAN UMR 7039, Blvd Aiguillettes,BP 70239, F-54506 Vandoeuvre Les Nancy, France
来源
IFAC PAPERSONLINE | 2018年 / 51卷 / 11期
关键词
Semantic Interoperability; Large system; Formal Concept Analysis; Relational Concept Analysis;
D O I
10.1016/j.ifacol.2018.08.330
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Interoperability is a major stake for industry, and in general for all the systems, of any dimension, that need to share contents in every shape. It provides that the exchanges between different parts of different entities perform in a perfect way. Various problems could arise and let the interoperation difficult or impossible. One of those problems could be the presence of implicit knowledge in the systems models. This kind of problems can be faced through knowledge formalisation strategies. The Formal Concept Analysis (FCA) is a mathematical tool to represent the information in a structured and complete way. In this scientific work, we present an extension of the FCA, the Relational Concept Analysis, to reveal tacit knowledge hidden in multi contexts systems. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
引用
收藏
页码:1397 / 1402
页数:6
相关论文
共 50 条
  • [21] An application of formal concept analysis to semantic neural decoding
    Dominik Maria Endres
    Peter Földiák
    Uta Priss
    Annals of Mathematics and Artificial Intelligence, 2009, 57 : 233 - 248
  • [22] Exploring Old Arabic Remedies with Formal and Relational Concept Analysis
    Fokou, Vanessa
    El Haff, Karim
    Braud, Agnes
    Dolques, Xavier
    Le Ber, Florence
    Pitchon, Veronique
    CONCEPTUAL KNOWLEDGE STRUCTURES, CONCEPTS 2024, 2024, 14914 : 302 - 318
  • [23] Computing semantic relatedness using latent semantic analysis and fuzzy formal concept analysis
    Jain S.
    Seeja K.R.
    Jindal R.
    Jain, Shivani (shivanijain13@gmail.com), 1600, Inderscience Publishers (13): : 92 - 100
  • [24] Relational, structural, and semantic analysis of graphical representations and concept maps
    Dirk Ifenthaler
    Educational Technology Research and Development, 2010, 58 : 81 - 97
  • [25] Relational, structural, and semantic analysis of graphical representations and concept maps
    Ifenthaler, Dirk
    ETR&D-EDUCATIONAL TECHNOLOGY RESEARCH AND DEVELOPMENT, 2010, 58 (01): : 81 - 97
  • [26] Semantic Web Ontology integration based on Formal Concept Analysis
    Xia, Hong
    MECHATRONICS, ROBOTICS AND AUTOMATION, PTS 1-3, 2013, 373-375 : 1714 - 1718
  • [27] An semantic rank for web crawler based on formal concept analysis
    Du, Yajun
    Li, Xinchun
    PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS AND KNOWLEDGE ENGINEERING (ISKE 2007), 2007,
  • [28] Formal concept analysis for an e-learning semantic web
    Beydoun, Ghassan
    EXPERT SYSTEMS WITH APPLICATIONS, 2009, 36 (08) : 10952 - 10961
  • [29] Semantic ranking of web pages based on formal concept analysis
    Du, Yajun
    Hai, YuFeng
    JOURNAL OF SYSTEMS AND SOFTWARE, 2013, 86 (01) : 187 - 197
  • [30] Discovering Relational Implications in Multilayer Networks Using Formal Concept Analysis
    Ghawi, Raji
    Pfeffer, Juergen
    INFORMATION INTEGRATION AND WEB INTELLIGENCE, IIWAS 2022, 2022, 13635 : 352 - 366