Abstract
We consider an application scenario where user want to find regions that have similar tendency about a certain issue, e.g., looking for regions that are neutral to new welfare policies. Motivated by this, we present a novel query to retrieve regions with similar tendency, named ρ-Dense Region Query (ρ-DR Query), that returns arbitrary shape of regions whose tendency satisfy the ρ-dense constraint. We design a basic algorithm to find all regions with similar spatial textual density that we define in this paper, and also propose an advanced algorithm that performs more efficiently. We conduct experiments to evaluate the performance of both algorithms, and the experiments prove the advanced algorithm is superior to the basic algorithm.
| Original language | English |
|---|---|
| Title of host publication | Advances in Computer Science and Ubiquitous Computing, CSA-CUTE 2018 |
| Editors | James J. Park, Doo-Soon Park, Young-Sik Jeong, Yi Pan |
| Publisher | Springer |
| Pages | 42-47 |
| Number of pages | 6 |
| ISBN (Print) | 9789811393402 |
| DOIs | |
| Publication status | Published - 2020 Jan 1 |
| Event | 10th International Conference on Computer Science and its Applications, CSA 2018 and the 13th KIPS International Conference on Ubiquitous Information Technologies and Applications, CUTE 2018 - Kuala Lumpre, Malaysia Duration: 2018 Dec 17 → 2018 Dec 19 |
Publication series
| Name | Lecture Notes in Electrical Engineering |
|---|---|
| Volume | 536 LNEE |
| ISSN (Print) | 1876-1100 |
| ISSN (Electronic) | 1876-1119 |
Conference
| Conference | 10th International Conference on Computer Science and its Applications, CSA 2018 and the 13th KIPS International Conference on Ubiquitous Information Technologies and Applications, CUTE 2018 |
|---|---|
| Country | Malaysia |
| City | Kuala Lumpre |
| Period | 18/12/17 → 18/12/19 |
Fingerprint
Keywords
- Geo-tagged data
- Region retrieval
- Spatial textual query
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering
Cite this
The Retrieval of Regions with Similar Tendency in Geo-Tagged Dataset. / Lim, Taehyung; Choi, Woosung; Kim, Minseok; Lee, Taemin; Jung, Soonyoung.
Advances in Computer Science and Ubiquitous Computing, CSA-CUTE 2018. ed. / James J. Park; Doo-Soon Park; Young-Sik Jeong; Yi Pan. Springer, 2020. p. 42-47 (Lecture Notes in Electrical Engineering; Vol. 536 LNEE).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - The Retrieval of Regions with Similar Tendency in Geo-Tagged Dataset
AU - Lim, Taehyung
AU - Choi, Woosung
AU - Kim, Minseok
AU - Lee, Taemin
AU - Jung, Soonyoung
PY - 2020/1/1
Y1 - 2020/1/1
N2 - We consider an application scenario where user want to find regions that have similar tendency about a certain issue, e.g., looking for regions that are neutral to new welfare policies. Motivated by this, we present a novel query to retrieve regions with similar tendency, named ρ-Dense Region Query (ρ-DR Query), that returns arbitrary shape of regions whose tendency satisfy the ρ-dense constraint. We design a basic algorithm to find all regions with similar spatial textual density that we define in this paper, and also propose an advanced algorithm that performs more efficiently. We conduct experiments to evaluate the performance of both algorithms, and the experiments prove the advanced algorithm is superior to the basic algorithm.
AB - We consider an application scenario where user want to find regions that have similar tendency about a certain issue, e.g., looking for regions that are neutral to new welfare policies. Motivated by this, we present a novel query to retrieve regions with similar tendency, named ρ-Dense Region Query (ρ-DR Query), that returns arbitrary shape of regions whose tendency satisfy the ρ-dense constraint. We design a basic algorithm to find all regions with similar spatial textual density that we define in this paper, and also propose an advanced algorithm that performs more efficiently. We conduct experiments to evaluate the performance of both algorithms, and the experiments prove the advanced algorithm is superior to the basic algorithm.
KW - Geo-tagged data
KW - Region retrieval
KW - Spatial textual query
UR - http://www.scopus.com/inward/record.url?scp=85076861311&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85076861311&partnerID=8YFLogxK
U2 - 10.1007/978-981-13-9341-9_8
DO - 10.1007/978-981-13-9341-9_8
M3 - Conference contribution
AN - SCOPUS:85076861311
SN - 9789811393402
T3 - Lecture Notes in Electrical Engineering
SP - 42
EP - 47
BT - Advances in Computer Science and Ubiquitous Computing, CSA-CUTE 2018
A2 - Park, James J.
A2 - Park, Doo-Soon
A2 - Jeong, Young-Sik
A2 - Pan, Yi
PB - Springer
ER -