A Method for k Nearest Neighbor Query of Line Segment in Obstructed Spaces Article Swipe
Liping Zhang
,
Song Li
,
Yingying Guo
,
Xiaohong Hao
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.3745/jips.04.0167
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.3745/jips.04.0167
In order to make up the deficiencies of the existing research results which cannot effectively deal with the nearest neighbor query based on the line segments in obstacle space, the k nearest neighbor query method of line segment in obstacle space is proposed and the STA_OLkNN algorithm under the circumstance of static obstacle data set is put forward. The query process is divided into two stages, including the filtering process and refining process. In the filtration process, according to the properties of the line segment Voronoi diagram, the corresponding pruning rules are proposed and the filtering algorithm is presented. In the refining process, according to the relationship of the position between the line segments, the corresponding distance expression method is put forward and the final result is obtained by comparing the distance. Theoretical research and experimental results show that the proposed algorithm can effectively deal with the problem of k nearest neighbor query of the line segment in the obstacle environment.
Related Topics
Concepts
k-nearest neighbors algorithm
Computer science
Voronoi diagram
Process (computing)
Line segment
Pruning
Line (geometry)
Obstacle
Set (abstract data type)
Space (punctuation)
Algorithm
Expression (computer science)
Data mining
Pattern recognition (psychology)
Artificial intelligence
Mathematics
Operating system
Geometry
Programming language
Biology
Political science
Law
Agronomy
Metadata
- Type
- article
- Language
- en
- Landing Page
- http://jips-k.org/digital-library/detail/16/2/12
- OA Status
- green
- Cited By
- 4
- Related Works
- 20
- OpenAlex ID
- https://openalex.org/W3029702753
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3029702753Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3745/jips.04.0167Digital Object Identifier
- Title
-
A Method for k Nearest Neighbor Query of Line Segment in Obstructed SpacesWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-04-01Full publication date if available
- Authors
-
Liping Zhang, Song Li, Yingying Guo, Xiaohong HaoList of authors in order
- Landing page
-
https://jips-k.org/digital-library/detail/16/2/12Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://jips-k.org/digital-library/detail/16/2/12Direct OA link when available
- Concepts
-
k-nearest neighbors algorithm, Computer science, Voronoi diagram, Process (computing), Line segment, Pruning, Line (geometry), Obstacle, Set (abstract data type), Space (punctuation), Algorithm, Expression (computer science), Data mining, Pattern recognition (psychology), Artificial intelligence, Mathematics, Operating system, Geometry, Programming language, Biology, Political science, Law, AgronomyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
4Total citation count in OpenAlex
- Citations by year (recent)
-
2023: 3, 2021: 1Per-year citation counts (last 5 years)
- Related works (count)
-
20Other works algorithmically related by OpenAlex
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| abstract_inverted_index.effectively | 14, 143 |
| abstract_inverted_index.circumstance | 49 |
| abstract_inverted_index.deficiencies | 6 |
| abstract_inverted_index.environment. | 160 |
| abstract_inverted_index.experimental | 135 |
| abstract_inverted_index.relationship | 106 |
| abstract_inverted_index.corresponding | 88, 115 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 4 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/15 |
| sustainable_development_goals[0].score | 0.4099999964237213 |
| sustainable_development_goals[0].display_name | Life in Land |
| citation_normalized_percentile.value | 0.66741182 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |