TK-SK: textual-restricted K spatial keyword query on road networks

Xiaopeng Kuang, Pengpeng Zhao*, Victor S. Sheng, Jian Wu, Zhixu Li, Guanfeng Liu, Zhiming Cui

*Corresponding author for this work

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

2 Citations (Scopus)

Abstract

With the rapid development of GPS-enabled devices, spatial keyword query, considering both spatial proximity to a query location and the textual relevance to the query keywords, is applied to many real-world applications. In this context, we study a specific type of spatial keyword query Textual-restricted K Spatial Keyword query (TK-SK query), which returns the nearest k points of interest (POIs) whose textual description is not less than a specified textual relevance threshold and whose location is close to the query location. We further propose a baseline approach and two advanced approaches (a separated index approach and a hybrid index approach) with different indexing strategies to solve this problem. Our comprehensive experiments conducted on real spatial datasets clearly demonstrate the efficiency of our two advanced approaches.

Original languageEnglish
Title of host publicationDatabases Theory and Applications
Subtitle of host publication26th Australasian Database Conference, ADC 2015, Proceedings
EditorsMohamed A. Sharaf, Muhammad Aamir Cheema, Jianzhong Qi
PublisherSpringer, Springer Nature
Pages167-179
Number of pages13
ISBN (Electronic)9783319195483
ISBN (Print)9783319195476
DOIs
Publication statusPublished - 2015
Externally publishedYes
Event26th Australasian Database Conference, ADC 2015 - Melbourne, Australia
Duration: 4 Jun 20157 Jun 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9093
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other26th Australasian Database Conference, ADC 2015
Country/TerritoryAustralia
CityMelbourne
Period4/06/157/06/15

Keywords

  • Hybrid index
  • Road networks
  • Spatial query

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