一种动态更新知识体系模型及其在专题信息采集中的应用研究

A Knowledge System Model of the Dynamic Update Application in Collecting Thematic Information

专题信息采集通常是指基于专题内容概念从海量网络信息资源里获取专门所需信息的过程，专题内容概念主要通过系统的领域知识体系来表达。但依据领域知识体系进行信息采集，需要人工手动更新领域知识，效率较低、查全率不高。本文尝试引入一种半自动动态更新领域知识体系方案来指导专题信息采集，通过基于关联规则的扩展查询改进算法来发现新的领域知识关键词，通过人工半自动化筛选，形成一种知识描述模型，设计并应用于EMALS的网络信息发现系统。最后通过实验证明知识动态演进方案是可行的。

Thematic information gathering is a process which is often based on the concept of thematic content to obtain special information from the massive online information, and the concept of thematic content is often expressed by the domain knowledge system. However, if we collect information using domain knowledge system, we have to update the knowledge manually. The efficiency of this method is low and recall rate is not high. This paper attempts to guide thematic information gathering by introducing a domain knowledge system of semi-automatic update to discover some new knowledge keywords through extended query improved algorithm based on association rules, and to form a knowledge model through artificial and semi-automatic selection, which is then designed and applied to network information discovery systems of EMALS. Finally, we prove the knowledge program of the dynamic evolution is feasible through experiments.