%0 Journal Article
%T Research on data mining model for obtaining and representing fishery knowledge<br>一种获取渔场知识的数据挖掘模型及知识表示方法研究*
%A 袁红春
%A 汤鸿益
%A 陈新军b
%J 计算机应用研究
%D 2010
%I 
%X This paper proposed a new knowledge discovery and representation model for fishery, which took three steps. Firstly, it extracted static knowledge from database by SVM (support vector machine) and fuzzy classifier. Secondly, it used extension data mining method to transfer static knowledge into dynamic knowledge. Thirdly, it established an ontology knowledge base by utilizing a mapping mechanism between the dynamic knowledge and ontology. Using the proposed model building procedure, implemented a prototype system for fishery forecasting. Experimental results show that the proposed method is effective and efficient.
%K knowledge discovery
%K extension data mining
%K ontology
%K thunnus obesus
%K fishery forecasting<br>知识发现
%K 可拓数据挖掘
%K 本体
%K 印度洋大眼金枪鱼
%K 渔情预测
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=0BFB767F4DF67405885CB4688EDE6D54&yid=140ECF96957D60B2&vid=DB817633AA4F79B9&iid=59906B3B2830C2C5&sid=FB236E900A861D0B&eid=9833A977204866B9&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=9