Ontology Based Decision Problem Semantic Analysis and Refining

doi:10.3969/j.issn.0372-2112.2012.08.017

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Ontology Based Decision Problem Semantic Analysis and Refining

更新时间：2025-07-08

- Ontology Based Decision Problem Semantic Analysis and Refining
- Acta Electronica Sinica Vol. 40, Issue 8, Pages: 1603-1608(2012)
- 作者机构：
  
  1. 上海师范大学信息与机电工程学院,上海,200234
  2. 同济大学电信学院,上海,201804
  3. 上海师范大学信息与机电工程学院,上海,200234
  4. 同济大学电信学院,上海,201804
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.61103069, No.71171148)
- DOI：10.3969/j.issn.0372-2112.2012.08.017
  CLC： TP302.7
- Published：2012
- 稿件说明：
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Ontology Based Decision Problem Semantic Analysis and Refining[J]. Acta Electronica Sinica, 2012, 40(8): 1603-1608.
DOI：

Ontology Based Decision Problem Semantic Analysis and Refining[J]. Acta Electronica Sinica, 2012, 40(8): 1603-1608. DOI： 10.3969/j.issn.0372-2112.2012.08.017.

摘要

理解复杂决策问题的关键在于使决策问题所包含的领域、目标、状态、结构等信息被系统所读懂.本文利用本体表达语义

实现了问题语义关系表示和语义计算.在保持理解结果不变的原则上

本文提出利用语义迭代方法将计算机无法理解的问题语义转化为可完全理解的语义.本文给出了语义精炼方法并形成最优闭合问题空间

在结构复杂度和内容复杂度两方面具有最低复杂度.实验分析表明

本文提出的复杂决策问题语义理解方法是有效的.

Abstract

A key challenge of complicated decision problem understanding is to make the information of decision problem

i.e.domain

goal

status and structure

readable and understandable for decision support system.This paper introduces ontology to describe semantics

and then problem semantic relationship and semantic computation are presented.Based on the rule of keeping the understanding results unchanged

semantic iteration method is addressed in order to transform the decision problem semantics

which cannot be analyzed through ontology

into fully understandable problem semantic.Further

semantic refining method is presented so that each complicated decision problem space can be refined into a most optimized closed problem space with a minimum complexity

which can be calculated from two facets:structure complexity and content complexity of problem space.Experiments show that the method of complicated decision problem semantic analysis is effective and feasible.

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Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education

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Department of Computer ScienceSUN Yat-sen UniversityGuangzhouGuangdong 510275China

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