吉林大学学报（信息科学版）2024，Vol.42Issue(4)：726-732,7.
基于多相似度模糊C均值聚类的不均衡流数据检索方法
Data Retrieval Method of Unbalanced Streaming Based on Multi-Similarity Fuzzy C-Means Clustering
摘要
Abstract
During the retrieval process of imbalanced stream data,the performance of data retrieval decreases due to the presence of imbalance in the data stream and the susceptibility to differential and edge data.In order to reduce the impact of the above factors,an imbalanced stream data retrieval method based on multi similarity fuzzy C-means clustering is proposed.This method calculates the multiple similarities between imbalanced flow data,and uses fuzzy C-means algorithm to cluster data with different similarities.By constructing a octree retrieval model,the data after clustering is stored,encoded and judged to complete the retrieval of unbalanced stream data.The experimental results show that the retrieval time of the proposed method is less than 20 seconds,and the recall and precision rates remain above 80％,with high NDCG(Normalized Discounted Cumulative Gain)values.关键词
标准特征矩阵/交叉类簇/数据编码筛选/不均衡度量/三维坐标/判断编码Key words
standard feature matrix/cross cluster/data encoding filter/unbalanced measure/3D coordinates/judgment code分类
信息技术与安全科学引用本文复制引用
韩云娜..基于多相似度模糊C均值聚类的不均衡流数据检索方法[J].吉林大学学报（信息科学版）,2024,42(4):726-732,7.基金项目
陕西省教育厅专项科研基金资助项目(20JK0950) （20JK0950）
