面向问题智能处理的基元-因素空间模型研究

互联网已成为获取信息的重要来源,但仅依靠信息搜索引擎等现有技术仍难以从海量信息中智能化挖掘知识为解决问题服务,面向问题处理的互联网知识搜索的模型与算法等问题一直未得到有效解决.知识搜索引擎要实现智能化解决问题的服务,关键是必须研究面向问题处理的互联网信息的智能重构模型.基元-因素空间模型以可拓学基元理论、因素空间理论和智能知识管理理论为基础,交叉研究从互联网海量信息资源中抽取对象、属性和量值,重组互联网信息,自动构建领域基元的方法及从领域信息中挖掘特定问题的因素空间以获取领域知识的智能算法.在动态基元信息、专家经验知识与因素空间融合的模式与算法基础上,开发模拟仿真软件以验证动态知识基元及因素库协同进行互联网信息重组的理论与方法,为利用互联网生成解决问题的创新策略和研发新一代面向问题处理的知识搜索引擎提供理论基础和新的方法支撑.

A Research on Problem Oriented Intelligent Processing Model by Basic-Element and Factor Space

The Internet has become an important way of obtaining information, but it is still difficult to provide aids to problem solving. Problem solving oriented knowledge searching in the Internet has not been solved thoroughly. The key factor is the reconstruction of web information. The combination of network and intelligence will bring the knowledge-based application of web information into a new stage. A cross-study is proposed on the novel hybrid method of extracting the objects, attributes, and values from the mass information of internet with simulation and automatically building the field basic elements on macro information based on Extenics, factor space theory and intelligent knowledge. In addition, a lot of future research directions are put forward, such as on intelligent algorithm which collects correlative factors of special problem from the field of information for acquiring domain knowledge. The research may provide theoretical basis and new methods for using the internet to generate the innovative strategy of problem solving and examine a new generation of problem-solving oriented knowledge search engine.