The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Cet article présente une méthode de raisonnement sur la structure des connaissances visuelles utilisant la carte thématique intelligente qui étend la structure de la carte thématique conventionnelle et améliore ses fonctions de raisonnement. La méthode de raisonnement visuel sur la structure des connaissances intègre deux types de raisonnement : le raisonnement par relation logique des connaissances et le raisonnement sur la structure des connaissances. Le raisonnement par relation logique de connaissances met en œuvre la vérification de la cohérence des connaissances et le raisonnement par associations implicites entre les points de connaissance. Nous proposons une stratégie de recherche de cercle d’unités de connaissances pour le raisonnement sur la structure des connaissances. Il implémente l'extension d'implication sémantique, l'extension sémantique pertinente et la confirmation d'appartenance à une classe sémantique. De plus, les résultats du raisonnement sur la structure des connaissances sont visualisés à l'aide d'ITM Toolkit. Un système prototype de raisonnement visuel sur la structure des connaissances a été mis en œuvre et appliqué à l'organisation, à la gestion et aux services massifs de connaissances pour l'éducation.
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Huimin LU, Boqin FENG, Xi CHEN, "Visual Knowledge Structure Reasoning with Intelligent Topic Map" in IEICE TRANSACTIONS on Information,
vol. E93-D, no. 10, pp. 2805-2812, October 2010, doi: 10.1587/transinf.E93.D.2805.
Abstract: This paper presents a visual knowledge structure reasoning method using Intelligent Topic Map which extends the conventional Topic Map in structure and enhances its reasoning functions. Visual knowledge structure reasoning method integrates two types of knowledge reasoning: the knowledge logical relation reasoning and the knowledge structure reasoning. The knowledge logical relation reasoning implements knowledge consistency checking and the implicit associations reasoning between knowledge points. We propose a Knowledge Unit Circle Search strategy for the knowledge structure reasoning. It implements the semantic implication extension, the semantic relevant extension and the semantic class belonging confirmation. Moreover, the knowledge structure reasoning results are visualized using ITM Toolkit. A prototype system of visual knowledge structure reasoning has been implemented and applied to the massive knowledge organization, management and service for education.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E93.D.2805/_p
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@ARTICLE{e93-d_10_2805,
author={Huimin LU, Boqin FENG, Xi CHEN, },
journal={IEICE TRANSACTIONS on Information},
title={Visual Knowledge Structure Reasoning with Intelligent Topic Map},
year={2010},
volume={E93-D},
number={10},
pages={2805-2812},
abstract={This paper presents a visual knowledge structure reasoning method using Intelligent Topic Map which extends the conventional Topic Map in structure and enhances its reasoning functions. Visual knowledge structure reasoning method integrates two types of knowledge reasoning: the knowledge logical relation reasoning and the knowledge structure reasoning. The knowledge logical relation reasoning implements knowledge consistency checking and the implicit associations reasoning between knowledge points. We propose a Knowledge Unit Circle Search strategy for the knowledge structure reasoning. It implements the semantic implication extension, the semantic relevant extension and the semantic class belonging confirmation. Moreover, the knowledge structure reasoning results are visualized using ITM Toolkit. A prototype system of visual knowledge structure reasoning has been implemented and applied to the massive knowledge organization, management and service for education.},
keywords={},
doi={10.1587/transinf.E93.D.2805},
ISSN={1745-1361},
month={October},}
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TY - JOUR
TI - Visual Knowledge Structure Reasoning with Intelligent Topic Map
T2 - IEICE TRANSACTIONS on Information
SP - 2805
EP - 2812
AU - Huimin LU
AU - Boqin FENG
AU - Xi CHEN
PY - 2010
DO - 10.1587/transinf.E93.D.2805
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E93-D
IS - 10
JA - IEICE TRANSACTIONS on Information
Y1 - October 2010
AB - This paper presents a visual knowledge structure reasoning method using Intelligent Topic Map which extends the conventional Topic Map in structure and enhances its reasoning functions. Visual knowledge structure reasoning method integrates two types of knowledge reasoning: the knowledge logical relation reasoning and the knowledge structure reasoning. The knowledge logical relation reasoning implements knowledge consistency checking and the implicit associations reasoning between knowledge points. We propose a Knowledge Unit Circle Search strategy for the knowledge structure reasoning. It implements the semantic implication extension, the semantic relevant extension and the semantic class belonging confirmation. Moreover, the knowledge structure reasoning results are visualized using ITM Toolkit. A prototype system of visual knowledge structure reasoning has been implemented and applied to the massive knowledge organization, management and service for education.
ER -