Locality sensitive hashing based searching scheme for a massive database

Haiying Shen, Ting Li, Ze Li, F. Ching
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引用次数: 12

Abstract

The rapid growth of information nowadays makes efficient information searching increasingly important for a massive database with tremendous volume of information. Traditional methods either rely on linear searching or depend on a tree structure. These methods search information in the entire database and compare a query with the records in the database during the searching process, which lead to inefficiency. This paper presents a locality sensitive hashing based searching scheme (LSS) to achieve highly efficient information searching in a massive database. LSS classifies information based on their similarities to facilitate fast information location. Based on the study and analysis of LSS, an improved scheme is further proposed to enhance the searching efficiency. Simulation results demonstrate the efficiency and effectiveness of the LSS schemes in searching information. They yield significant improvements over the efficiency of traditional methods. In addition, they guarantee successful location of the queried records.
基于位置敏感哈希的海量数据库搜索方案
在信息飞速增长的今天,对于一个信息量巨大的数据库来说,高效的信息搜索变得越来越重要。传统的方法要么依赖于线性搜索,要么依赖于树结构。这些方法在整个数据库中搜索信息,并在搜索过程中将查询与数据库中的记录进行比较,从而导致效率低下。为了在海量数据库中实现高效的信息搜索,提出了一种基于局部敏感哈希的搜索方案。LSS根据信息的相似性对信息进行分类,便于快速定位信息。在对LSS进行研究和分析的基础上,进一步提出了一种改进方案,以提高搜索效率。仿真结果验证了LSS方案在搜索信息方面的效率和有效性。它们大大提高了传统方法的效率。此外,它们保证查询记录的成功定位。
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