网站信息分类体系优化方法及其应用
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摘要
本文的研究主题是网站信息分类体系优化方法及其在林业政务网站中的应用。主要研究内容包括:
(1)在分析网站信息分类体系优化内涵、目标和原则的基础上,用公式描述网站信息分类体系优化问题模型。将网站信息分类体系优化问题转化成多目标决策问题,并提出分析、评价、设计、实现四阶段网站信息分类体系优化方法。
(2)提出网站信息分类体系质量评价指标体系,并用该体系评价了国家林业局网站现有信息分类体系的质量;提出网站信息分类体系处理过程成熟度模型和网站信息分类体系管理水平评价方法。
(3)提出网站信息分类体系优化方案设计方法,该方法可以细分为特征优化、粒度优化、命名优化、结构优化等环节。通过系统分析和对我国林业电子政务网站的实证分析提出网站八种信息分类模式,并提出自顶向下特征优化方法。还提出了粗粒度优先粒度优化方法和基于统计的命名优化方法、基于交互式遗传算法的交互式命名优化方法。总结出网站信息分类体系理想结构特点,并提出自底向上逐层结构优化方法和基于遗传算法整体结构优化方法。
(4)应用本文方法优化国家林业局网站现有的信息分类体系,并对比了优化前后的信息分类体系。
The topic of the dissertation is optimizing method of Website’s Information Classification (WIC) and its application in forestry E-governments websites. The contributions of the dissertation are as follows:
(1) The dissertation analyses the definition, aims and principles of optimizing WIC, firstly. Based on these, the mathematic formula model of optimizing WIC is given. With changing the Optimizing WIC problem into the Multi- Objective Decision Making (MODM) problem, the dissertation brings up a method for optimizing WIC. The method has four steps which are analysis, assessing, design and implementation.
(2) The dissertation brings up an indicator system for assessing Website’s Information Classification Quality (WICQ), and assesses the WICQ of Chinese State Forestry Administration website with the indicator system. After this work, the dissertation brings up maturity model of processing procedure on WIC and a method for assessing managing level of WIC.
(3) The dissertation brings up a method for designing the optimizing plan on WIC which has four steps. These steps are feature optimizing, granularity optimizing, name optimizing and structure optimizing. With systematic analysis and empirical analysis of Chinese forestry E-governments websites, the dissertation finds eight classification models for web information. Then, the dissertation brings up a top-down feature optimizing method. The dissertation brings up a granularity optimizing method which selects the biggest granularity firstly. The dissertation brings up two methods which take advantage of statistics and interactive genetic algorithm (IGA) respectively for name optimizing. For optimizing structure, the dissertation generalizes the feature of perfect WIC structure and brings up two methods. One method optimizes the WIC structure level by level, while the other method optimizes the structure just one time which basing on genetic algorithm (GA).
(4) The dissertation optimizes the WIC of Chinese State Forestry Administration website with the method which is mentioned in this dissertation. Then, the new WIC and the old WIC are compared.
(1)在分析网站信息分类体系优化内涵、目标和原则的基础上,用公式描述网站信息分类体系优化问题模型。将网站信息分类体系优化问题转化成多目标决策问题,并提出分析、评价、设计、实现四阶段网站信息分类体系优化方法。
(2)提出网站信息分类体系质量评价指标体系,并用该体系评价了国家林业局网站现有信息分类体系的质量;提出网站信息分类体系处理过程成熟度模型和网站信息分类体系管理水平评价方法。
(3)提出网站信息分类体系优化方案设计方法,该方法可以细分为特征优化、粒度优化、命名优化、结构优化等环节。通过系统分析和对我国林业电子政务网站的实证分析提出网站八种信息分类模式,并提出自顶向下特征优化方法。还提出了粗粒度优先粒度优化方法和基于统计的命名优化方法、基于交互式遗传算法的交互式命名优化方法。总结出网站信息分类体系理想结构特点,并提出自底向上逐层结构优化方法和基于遗传算法整体结构优化方法。
(4)应用本文方法优化国家林业局网站现有的信息分类体系,并对比了优化前后的信息分类体系。
The topic of the dissertation is optimizing method of Website’s Information Classification (WIC) and its application in forestry E-governments websites. The contributions of the dissertation are as follows:
(1) The dissertation analyses the definition, aims and principles of optimizing WIC, firstly. Based on these, the mathematic formula model of optimizing WIC is given. With changing the Optimizing WIC problem into the Multi- Objective Decision Making (MODM) problem, the dissertation brings up a method for optimizing WIC. The method has four steps which are analysis, assessing, design and implementation.
(2) The dissertation brings up an indicator system for assessing Website’s Information Classification Quality (WICQ), and assesses the WICQ of Chinese State Forestry Administration website with the indicator system. After this work, the dissertation brings up maturity model of processing procedure on WIC and a method for assessing managing level of WIC.
(3) The dissertation brings up a method for designing the optimizing plan on WIC which has four steps. These steps are feature optimizing, granularity optimizing, name optimizing and structure optimizing. With systematic analysis and empirical analysis of Chinese forestry E-governments websites, the dissertation finds eight classification models for web information. Then, the dissertation brings up a top-down feature optimizing method. The dissertation brings up a granularity optimizing method which selects the biggest granularity firstly. The dissertation brings up two methods which take advantage of statistics and interactive genetic algorithm (IGA) respectively for name optimizing. For optimizing structure, the dissertation generalizes the feature of perfect WIC structure and brings up two methods. One method optimizes the WIC structure level by level, while the other method optimizes the structure just one time which basing on genetic algorithm (GA).
(4) The dissertation optimizes the WIC of Chinese State Forestry Administration website with the method which is mentioned in this dissertation. Then, the new WIC and the old WIC are compared.
引文
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