%0 Journal Article
%T A Model for Mixed Attributions Cases Indexing<br>一个混合属性的实例检索模型
%A ZHONG Shi-sheng
%A WANG Zhi-xing
%A HE Xin-gui
%A <br>钟诗胜
%A 王知行
%A 何新贵
%J 软件学报
%D 1999
%I 
%X In this paper, the disadvantages of the existi ng cases indexing models are analyzed. A new kind of cases indexing model for mi xed attributions cases indexing based on fuzzy analogy preferred ratio is presen ted. This model uses fuzzy distance to describe the similar degree between the c orresponding attributions of two cases and is suitable for numerical, linguistic and mixed attributions cases indexing.
%K AI(artificial intelligent)
%K CBR(case-ba sed reasoning)
%K fuzzy analogy preferred ratio
%K mixed attribution cases indexing
%K fuzzy distance<br>人工智能
%K 基于实例的推理
%K 模糊相似优先比
%K 混合属性实例检索
%K 语义距离
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=7735F413D429542E610B3D6AC0D5EC59&aid=D3A8A2975A71B9FE&yid=B914830F5B1D1078&vid=F3090AE9B60B7ED1&iid=94C357A881DFC066&sid=68FF5306A8F9C315&eid=E3D3D8D1B650AE1E&journal_id=1000-9825&journal_name=软件学报&referenced_num=16&reference_num=9