【摘 要】
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Approximate Nearest Neighbor(ANN)search in high dimensional space has become a fundamental paradigm in many applications.Recently,Locality Sensitive Hashing
【出 处】
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第七届国际博士生论坛暨青年教师发展研讨会
论文部分内容阅读
Approximate Nearest Neighbor(ANN)search in high dimensional space has become a fundamental paradigm in many applications.Recently,Locality Sensitive Hashing(LSH)and its variants are acknowledged as the most promising solutions to ANN search.However,state-of-the-art LSH approaches suffer from a drawback: accesses to candidate objects require a large number of random I/O operations.In order to guarantee the quality of returned results,sufficient objects should be verified,which would consume enormous I/O cost.
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