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基于本体的决策问题语义理解及精炼方法

张波1,2, 向阳2, 黄震华2   

  1. 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
  • 收稿日期:2010-11-23 修回日期:2012-01-01 出版日期:2012-08-25 发布日期:2012-08-25
  • 作者简介:张 波 1978年生于江苏省常州市.现为上海师范大学讲师,同济大学电信学院博士后.主要研究方向为本体论,决策支持系统等. E-mail:06zhangbo@tongji.edu.cn向 阳 1962年生,教授,博士生导师,主要研究方向为决策支持系统,数据挖掘与计算智能等.黄震华 1982年生,副研究员,主要研究方向为语义计算、数据库、数据挖掘等.
  • 基金资助:

    国家自然科学基金(No.61103069,No.71171148)

Ontology Based Decision Problem Semantic Analysis and Refining

ZHANG Bo1,2, XIANG Yang2, HUANG Zhen-hua2   

  1. 1. College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China;
    2. College of Electronics and Information Engineering, Tongji University, Shanghai 201804, China
  • Received:2010-11-23 Revised:2012-01-01 Online:2012-08-25 Published:2012-08-25

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.

关键词: 本体, 语义理解, 语义迭代, 语义精炼, 最优闭合问题空间

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.

Key words: ontology, semantics understanding, semantics iteration, semantics refining, most optimized closed problem space

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