Proceedings of the First International Conference on Advances in Computer Vision and Artificial Intelligence Technologies (ACVAIT 2022)

<Previous Article In Volume
Next Article In Volume>

Comparative Study of Grid-Inverted List Hybrid Indexing Techniques for Moving Objects and Queries

Authors
Sulbha Powar1, *, Ganesh Magar1
1P. G. Department of Computer Science, SNDT Women’s University, Mumbai, India
*Corresponding author. Email: sulbha_powar@hotmail.com
Corresponding Author
Sulbha Powar
Available Online 10 August 2023.
DOI
10.2991/978-94-6463-196-8_19How to use a DOI?
Keywords
Conceptual Partitioning; Geo-Textual data; Grid Index; Hybrid Index; Inverted List; Moving objects; Nearest Neighbour
Abstract

Advancement in GPS technologies and availability of a variety of devices to capture location and other attributes of the objects has led to an enormous development in geo-textual data. Searching through these objects for relevant objects as per the requirement needs efficient indexing technique and searching algorithm. Past queries, Present queries and Future queries are the three types of geo-textual queries. Past queries are responded based on the historical locations of the moving objects stored in the database. Future queries can be answered if the velocity vector of the object is known in advance. But in many real-time applications the position of the objects in future cannot be predicted. In such a scenario capturing movement of the objects and queries in real time and answering queries or updating query answer sets in real time is essential. In this paper three different techniques based on grid index, modified to handle geo-textual queries using hybrid index, YPK-CNN, SEA-CNN and CPM to handle real time queries, are presented. The methods to find kNN based on these three techniques are proposed in this paper and are also compared. Conceptual partitioning along with hybrid index improve the query performance by 30 to 40%.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the First International Conference on Advances in Computer Vision and Artificial Intelligence Technologies (ACVAIT 2022)
Series
Advances in Intelligent Systems Research
Publication Date
10 August 2023
ISBN
10.2991/978-94-6463-196-8_19
ISSN
1951-6851
DOI
10.2991/978-94-6463-196-8_19How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Sulbha Powar
AU  - Ganesh Magar
PY  - 2023
DA  - 2023/08/10
TI  - Comparative Study of Grid-Inverted List Hybrid Indexing Techniques for Moving Objects and Queries
BT  - Proceedings of the First International Conference on Advances in Computer Vision and Artificial Intelligence Technologies (ACVAIT 2022)
PB  - Atlantis Press
SP  - 230
EP  - 249
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-196-8_19
DO  - 10.2991/978-94-6463-196-8_19
ID  - Powar2023
ER  -