Area Queries Based on Voronoi Diagrams
December 01, 2019 ยท Declared Dead ยท ๐ IEEE International Conference on Data Engineering
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Yang Li
arXiv ID
1912.00426
Category
cs.DB: Databases
Citations
8
Venue
IEEE International Conference on Data Engineering
Last Checked
3 months ago
Abstract
The area query, to find all elements contained in a specified area from a certain set of spatial objects, is a very important spatial query widely required in various fields. A number of approaches have been proposed to implement this query, the best known of which is to obtain a rough candidate set through spatial indexes and then refine the candidates through geometric validations to get the final result. When the shape of the query area is a rectangle, this method has very high efficiency. However, when the query area is irregular, the candidate set is usually much larger than the final result set, which means a lot of redundant detection needs to be done, thus the efficiency is greatly limited. In view of this issue, we propose a method of iteratively generating candidates based on Voronoi diagrams and apply it to area queries. The experimental results indicate that with our approach, the number of candidates in the process of area query is greatly reduced and the efficiency of the query is significantly improved.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Databases
R.I.P.
๐ป
Ghosted
R.I.P.
๐ป
Ghosted
The Case for Learned Index Structures
R.I.P.
๐ป
Ghosted
Untangling Blockchain: A Data Processing View of Blockchain Systems
R.I.P.
๐ป
Ghosted
Converting Static Image Datasets to Spiking Neuromorphic Datasets Using Saccades
R.I.P.
๐ป
Ghosted
BLOCKBENCH: A Framework for Analyzing Private Blockchains
R.I.P.
๐ป
Ghosted
Data Synthesis based on Generative Adversarial Networks
Died the same way โ ๐ป Ghosted
R.I.P.
๐ป
Ghosted
Language Models are Few-Shot Learners
R.I.P.
๐ป
Ghosted
PyTorch: An Imperative Style, High-Performance Deep Learning Library
R.I.P.
๐ป
Ghosted
XGBoost: A Scalable Tree Boosting System
R.I.P.
๐ป
Ghosted