郑州大学学报（理学版）2026，Vol.58Issue(3)：77-85,9.DOI:10.13705/j.issn.1671-6841.2024172
知识服务中基于WKNN-MF与NRS的非完备案例知识匹配
Incomplete Case Knowledge Matching Based on WKNN-MF and NRS in Knowledge Service Process
摘要
Abstract
To improve the benefits of knowledge services and solve the problem of missing attribute values of incomplete case knowledge,a knowledge matching method based on WKNN-MF and NRS was de-signed.The WKNN algorithm was used to pre-populate the non-complete case knowledge set as the basis of MF calculation,and WKNN-MF was used to obtain the complete case knowledge set.On this basis,NRS simplification was performed to eliminate redundant attributes,and then similar cases were searched by the similarity of knowledge views to determine the knowledge matching results.Experimental results based on three different UCI datasets showed that the proposed method had a better filling effect on in-complete case knowledge sets compared with existing data-filling algorithms.关键词
知识服务/知识匹配/非完备案例知识/加权最近邻/缺失森林/邻域粗糙集Key words
knowledge service/knowledge matching/non-complete case knowledge/weighted KNN/missing forest/NRS分类
信息技术与安全科学引用本文复制引用
张建华,曹子傲,周晓倩,温丹丹,贺龙飞..知识服务中基于WKNN-MF与NRS的非完备案例知识匹配[J].郑州大学学报（理学版）,2026,58(3):77-85,9.基金项目
国家社会科学基金项目(19BTQ035) （19BTQ035）
