short-paper

Spatio-temporal keyword queries for moving objects

Authors:

SIGSPATIAL '15: Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems

Article No.: 55, Pages 1 - 4

https://doi.org/10.1145/2820783.2820845

Published: 03 November 2015 Publication History

Get Access

Abstract

Many applications involve queries that combine spatial, temporal and textual filters. In this paper, we address the problem of efficient evaluation of queries that perform spatial, temporal and keyword-based filtering on historical movement data of objects which are additionally associated with textual information in the form of keywords. Our work combines and builds upon concepts and techniques for spatio-temporal and spatio-textual queries, proposing two hybrid indexes for this purpose. An experimental evaluation of the proposed approaches is presented, using real-world datasets from two different types of sources.

References

[1]

V. P. Chakka, A. Everspaugh, and J. M. Patel. Indexing large trajectory data sets with SETI. In CIDR, 2003.

Google Scholar

[2]

L. Chen, G. Cong, C. S. Jensen, and D. Wu. Spatial keyword query processing: An experimental evaluation. PVLDB, 6(3):217--228, 2013.

Digital Library

Google Scholar

[3]

M. Christoforaki, J. He, C. Dimopoulos, A. Markowetz, and T. Suel. Text vs. space: efficient geo-search query processing. In CIKM, pages 423--432, 2011.

Digital Library

Google Scholar

[4]

G. Cong, H. Lu, B. C. Ooi, D. Zhang, and M. Zhang. Efficient spatial keyword search in trajectory databases. CoRR, abs/1205.2880, 2012.

Google Scholar

[5]

Y. Han, L. Wang, Y. Zhang, W. Zhang, and X. Lin. Spatial keyword range search on trajectories. In DASFAA, pages 223--240, 2015.

Crossref

Google Scholar

[6]

R. Hariharan, B. Hore, C. Li, and S. Mehrotra. Processing spatial-keyword (SK) queries in geographic information retrieval (GIR) systems. In SSDBM, page 16, 2007.

Digital Library

Google Scholar

[7]

M. F. Mokbel, T. M. Ghanem, and W. G. Aref. Spatio-temporal access methods. IEEE Data Eng. Bull., 26(2):40--49, 2003.

Google Scholar

[8]

S. Nepomnyachiy, B. Gelley, W. Jiang, and T. Minkus. What, where, and when: keyword search with spatio-temporal ranges. In GIR, pages 2:1--2:8, 2014.

Digital Library

Google Scholar

[9]

L. Nguyen-Dinh, W. G. Aref, and M. F. Mokbel. Spatio-temporal access methods: Part 2 (2003--2010). IEEE Data Eng. Bull., 33(2):46--55, 2010.

Google Scholar

[10]

B. Thomee, D. A. Shamma, G. Friedland, B. Elizalde, K. Ni, D. Poland, D. Borth, and L.-J. Li. The new data and new challenges in multimedia research. arXiv preprint arXiv:1503.01817, 2015.

Google Scholar

Cited By

View all

Liu SCong GFeng KGu WZhang F(2023)Effectiveness Perspectives and a Deep Relevance Model for Spatial Keyword QueriesProceedings of the ACM on Management of Data10.1145/35886911:1(1-25)Online publication date: 30-May-2023
https://doi.org/10.1145/3588691
Tang JLu XXiang YShi CGu J(2023)Blockchain search engine: Its current research status and future prospect in Internet of Things networkFuture Generation Computer Systems10.1016/j.future.2022.08.008138(120-141)Online publication date: Jan-2023
https://doi.org/10.1016/j.future.2022.08.008
Xu CZhu LBai LHe J(2023)Keywords Query of uncertain spatiotemporal data based on XMLEarth Science Informatics10.1007/s12145-023-00934-816:1(241-257)Online publication date: 13-Jan-2023
https://doi.org/10.1007/s12145-023-00934-8
Show More Cited By

Index Terms

Spatio-temporal keyword queries for moving objects
1. Human-centered computing
  1. Visualization
    1. Visualization application domains
      1. Geographic visualization
2. Information systems
  1. Information systems applications
    1. Spatial-temporal systems

Recommendations

Indexing moving objects for directions and velocities queries

Moving object databases are required to support different types of queries with a large number of moving objects. New types of queries namely directions and velocity queries (DV queries), are to be supported and covered. The TPR-tree and its successors ...
Efficient evaluation of continuous spatio-temporal queries on moving objects with uncertain velocity

Continuous Range (CR) query and Continuous K-Nearest Neighbor (CKNN) query are two important types of spatio-temporal queries. Given a time interval [t _s, t ...
Shadow: Answering Why-Not Questions on Top-K Spatial Keyword Queries over Moving Objects
Database Systems for Advanced Applications
Abstract
The popularity of mobile terminals has generated massive moving objects with spatio-textual characteristics. A top-k spatial keyword query over moving objects (Top-k SKM query) returns the top-k objects, moving or static, based on a ranking ...

Comments

Information & Contributors

Information

Published In

SIGSPATIAL '15: Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 2015

646 pages

ISBN:9781450339674

DOI:10.1145/2820783

General Chairs:
Mohamed Ali
University of Washington, Tacoma
,
Yan Huang
University of North Texas
,
Program Chairs:
Michael Gertz
Heidelberg University, Germany
,
Matthias Renz
LMU Munich, Germany
,
Jagan Sankaranarayanan
NEC Labs

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

In-Cooperation

SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 03 November 2015

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Short-paper

Conference

SIGSPATIAL'15

Sponsor:

SIGSPATIAL

SIGSPATIAL'15: 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 3 - 6, 2015

Washington, Seattle

Acceptance Rates

SIGSPATIAL '15 Paper Acceptance Rate 38 of 212 submissions, 18%;

Overall Acceptance Rate 257 of 1,238 submissions, 21%

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

12
Total Citations
View Citations
192
Total Downloads

Downloads (Last 12 months)8
Downloads (Last 6 weeks)1

Reflects downloads up to 08 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

View all

Liu SCong GFeng KGu WZhang F(2023)Effectiveness Perspectives and a Deep Relevance Model for Spatial Keyword QueriesProceedings of the ACM on Management of Data10.1145/35886911:1(1-25)Online publication date: 30-May-2023
https://doi.org/10.1145/3588691
Tang JLu XXiang YShi CGu J(2023)Blockchain search engine: Its current research status and future prospect in Internet of Things networkFuture Generation Computer Systems10.1016/j.future.2022.08.008138(120-141)Online publication date: Jan-2023
https://doi.org/10.1016/j.future.2022.08.008
Xu CZhu LBai LHe J(2023)Keywords Query of uncertain spatiotemporal data based on XMLEarth Science Informatics10.1007/s12145-023-00934-816:1(241-257)Online publication date: 13-Jan-2023
https://doi.org/10.1007/s12145-023-00934-8
Xu AZhang ZMa XZhang ZXu T(2022)Spatial Concept Query Based on Lattice-TreeISPRS International Journal of Geo-Information10.3390/ijgi1105031211:5(312)Online publication date: 15-May-2022
https://doi.org/10.3390/ijgi11050312
Gryllakis FPelekis NDoulkeridis CVarlamis ITheodoridis Y(2022)Social Spatio-temporal Keyword Pattern (S²KP) Queries in Multiple Aspect Trajectories DatabasesProceedings of the 34th International Conference on Scientific and Statistical Database Management10.1145/3538712.3538716(1-12)Online publication date: 6-Jul-2022
https://dl.acm.org/doi/10.1145/3538712.3538716
de Souza ARenso CPerego RBogorny V(2022)MAT‐Index: An index for fast multiple aspect trajectory similarity measuringTransactions in GIS10.1111/tgis.1288926:2(691-716)Online publication date: 20-Jan-2022
https://doi.org/10.1111/tgis.12889
Chen ZChen LCong GJensen C(2021)Location- and keyword-based querying of geo-textual data: a surveyThe VLDB Journal — The International Journal on Very Large Data Bases10.1007/s00778-021-00661-w30:4(603-640)Online publication date: 30-Mar-2021
https://dl.acm.org/doi/10.1007/s00778-021-00661-w
Tang JZhou ZXue XWang G(2020)Using Collaborative Edge-Cloud Cache for Search in Internet of ThingsIEEE Internet of Things Journal10.1109/JIOT.2019.29463897:2(922-936)Online publication date: Feb-2020
https://doi.org/10.1109/JIOT.2019.2946389
Tang JXue XYangui SZhou Z(2020)Efficient Search for Moving Object Devices in Internet of Things Networks2020 IEEE International Conference on Web Services (ICWS)10.1109/ICWS49710.2020.00067(454-462)Online publication date: Oct-2020
https://doi.org/10.1109/ICWS49710.2020.00067
Tang JZhou ZShu LHancke G(2019)SMPKR: Search Engine for Internet of ThingsIEEE Access10.1109/ACCESS.2019.29523907(163615-163625)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2952390
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Abstract

References

Cited By

Index Terms

Recommendations

Indexing moving objects for directions and velocities queries

Efficient evaluation of continuous spatio-temporal queries on moving objects with uncertain velocity

Shadow: Answering Why-Not Questions on Top-K Spatial Keyword Queries over Moving Objects

Comments

Information

Published In

Sponsors

In-Cooperation

Publisher

Publication History

Permissions

Check for updates

Author Tags

Qualifiers

Conference

Acceptance Rates

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

Login options

Full Access

View options

PDF

eReader

Share

Share this Publication link

Share on social media

Affiliations