Efficient Retrieval of Top-k Weighted Spatial Triangles

Taniguchi, Ryosuke; Amagata, Daichi; Hara, Takahiro

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2022, 13245, 224-231

Number of Access:845（2025-10-07 07:33 Counts）

Identifier to cite or link to this item: https://hdl.handle.net/11094/92844

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Title
Efficient Retrieval of Top-k Weighted Spatial Triangles
Creator
CreatorName
Taniguchi, Ryosuke
NRID
1000040770649 1000040770649
researchmap permalink
amgt amgt
Scopus Author ID
55811167300 55811167300
CreatorName
Amagata, Daichi
NRID
1000020294043 1000020294043
ORCID
0000-0003-4807-3156 0000-0003-4807-3156
researchmap permalink
hara-osakau hara-osakau
Scopus Author ID
7404213547 7404213547
CreatorName
Hara, Takahiro
Subject
Spatial points
Top-k retrieval
Weighted graph
Description
This version of the contribution has been accepted for publication, after peer review (when applicable) but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/978-3-031-00123-9_17.
Abstract
Due to the proliferation of location-based services and IoT devices, a lot of spatial points are being generated. Spatial data analysis is well known to be an important task. As spatial data analysis tools, graphs consisting of spatial points, where each point has edges to its nearby points and the weight of each edge is the distance between the corresponding points, have been receiving much attention. We focus on triangles (one of the simplest sub-graph patterns) in such graphs and address the problem of retrieving the top-k weighted spatial triangles. This problem has important real-life applications, e.g., group search, urban planning, and co-location pattern mining. However, this problem is computationally challenging, because the number of triangles in a graph is generally huge and enumerating all of them is not feasible. To solve this challenge, we propose an efficient algorithm that returns the exact result. Our experimental results on real datasets show the efficiency of our algorithm.
Conference Information
Conference Name
International Conference on Database Systems for Advanced Applications
Conference Sequence
27
Conference Date
April 11th 2022 to April 14th, 2022
Conference Venue
Online
Conference Place
Hyderabad
Conference Country
Publisher
Springer Science and Business Media Deutschland GmbH
Source Title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume (Issue)
13245
Page
224-231
Date of Issued
2022-04-08
Language
English
Handle URL
https://hdl.handle.net/11094/92844
Relation.isVersionOf
DOI (Publisher Version)
https://doi.org/10.1007/978-3-031-00123-9_17
Relation.isPartOf
ISBN
9783031001222
Access Rights
open access
CopyRight
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
oaire:version
Accepted Manuscript
Category
会議発表論文 Conference Paper