Based On Structured Text Sars Emergency Knowledge Management System Design And Implementation

The government is eager to the public health emergency management system after SARS broke. All kinds of knowledge is needed by makers in the process of decision-making. The makers can direct emergency resources correctly and timely using them. Knowledge exists in amount of texts published by the professional department of government. It is impossible that the makers command all knowledge. But they must make decisions quickly. So emergency knowledge management system is an important part of the public health emergency management system, and knowledge search is the core of it. Emergency knowledge management and search system is a system with the function that extracting some subject knowledge required by users from a great deal of texts. The knowledge is a text, a part of a text or a set of parts of texts. Text search models, such as vector space and so on, come and are applied in the systems querying texts. The methods are effective in getting the full texts. But every SARS text is long in content and multitudinous in subject, so the full texts can't make users satisfied at all. In order to get the subject knowledge passages, an effective method is that the SARS texts are structured in subject by virtue of users' requirement.In this paper, the process of SARS emergency management is firstly analyzed. A way to resolving SARS emergency question is induced. It is emphasized that knowledge is a key element in the way. For SARS problem, knowledge is classified by using multidimensional data model, and the relation of question and the subject of knowledge is built up. The system function frame on SARS knowledge management is proposed. Secondly, most texts are unstructured in subject and semi-structured in style. Four data models are designed for the structure of texts in subject based on object oriented. The method that texts are structured in subject by virtue of the style of texts is proposed. The logic program is designed for the query of SARS emergency knowledge. It is effective in the extraction for subject knowledge required from a great deal of texts. Lastly, based on software engineering method, the interfaces and databases are designed and the system is implemented with Visual C++ 6.0. The effective of system is validated in practice.