西安电子科技大学学报（自然科学版）Issue(1)：94-98,5.DOI:10.3969/j.issn.1001-2400.2016.01.017
一种相似性保持的线性嵌入哈希方法
Linear embedding Hashing method in preserving similarity
摘要
Abstract
In order to implement quick and effective search , save the storage space and improve the poor performance of affinity relationshaps between high dimensional data and its codes in image retrieval , a new linear embedding hashing is proposed by introducing the preserving similarity . First , the whole data set is clustered into several classes , and then the similarity predicted function is used to maintain affinity relationships between high dimensional data and its codes so as to establish the objective function . By minimizing the margin loss function , the optimal embedded matrix can be obtained . Compared with the existing classic hashing algorithm , experimental results show that the performance of the linear embedding hash algorithm is superior to the other binary encoding strategy on precision and recall .关键词
相似最近邻搜索/哈希/相关性预测函数/查准率/查全率Key words
approximate nearest neighbor search/hashing/similarity predicted function/precision/recall分类
信息技术与安全科学引用本文复制引用
王秀美,丁利杰,高新波..一种相似性保持的线性嵌入哈希方法[J].西安电子科技大学学报（自然科学版）,2016,(1):94-98,5.基金项目
国家杰出青年科学基金资助项目（61125204）；国家自然科学基金重点资助项目（61432014）；国家自然科学基金资助项目（6147230）；国家自然科学基金青年基金资助项目 （）
