Review of Approximate String Search in Spatial Dataset

Abstract

Many research articles and methods presented over the problem of approximate string search, however most this methods suffered from the accuracy and speed. Our work deals with the approximate string search in large spatial databases. Especially, this paper investigates range queries augmented with a string similarity search predicate in both euclidean space and road networks. This query is called spatial approximate string (SAS) query . This paper presents a  study for spatial approximate string queries in both the euclidean space and road networks. For ESAS query Spatial solution is done using MHR-tree, which embeds min-wise signatures into an R-tree in Euclidean space. For RSAS query, spatial solution is done using RSASSOL algorithm.