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Answering spatial approximate keyword queries in disks

  • ZTE Corporation
  • Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Spatial approximate keyword queries consist of a spatial condition and a set of keywords as the fuzzy textual conditions, and they return objects labeled with a set of keywords similar to queried keywords while satisfying the spatial condition. Such queries enable users to find objects of interest in a spatial database, and make mismatches between user query keywords and object keywords tolerant. With the rapid growth of data, spatial databases storing objects from diverse geographical regions can be no longer held in main memories. Thus, it is essential to answer spatial approximate keyword queries over disk resident datasets. Existing works present methods either returns incomplete answers or indexes in main memory, and effective solutions in disks are in demand. This paper presents a novel disk resident index RMB-tree to support spatial approximate keyword queries. We study the principle of augmenting R-tree with capacity of approximate keyword searching based on existing solutions, and store multiple bitmaps in R-tree nodes to build an RMB-tree. RMB-tree supports spatial conditions such as range constraint, combined with keyword similarity metrics such as edit distance, dice etc. Experimental results against R-tree on two real world datasets demonstrate the efficiency of our solution.

Original languageEnglish
Title of host publicationWeb Technologies and Applications - 17th Asia-PacificWeb Conference,APWeb 2015, Proceedings
EditorsReynold Cheng, Bin Cui, Zhenjie Zhang, Ruichu Cai, Jia Xu
PublisherSpringer Verlag
Pages424-436
Number of pages13
ISBN (Print)9783319252544
DOIs
StatePublished - 2015
Event17th Asia-PacificWeb Conference, APWeb 2015 - Guangzhou, China
Duration: 18 Sep 201520 Sep 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9313
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference17th Asia-PacificWeb Conference, APWeb 2015
Country/TerritoryChina
CityGuangzhou
Period18/09/1520/09/15

Keywords

  • Approximate search
  • Index structure
  • Query processing
  • Spatial database

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