An Adjusting Strategy after DBSCAN Article Swipe
Runfa Zhang
,
Jianlong Qiu
,
Ming Guo
,
Huixia Cui
,
Xiangyong Chen
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1016/j.ifacol.2022.05.038
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1016/j.ifacol.2022.05.038
DBSCAN is a popular density-based clustering algorithm in data mining. However, its principle of first come, first served to deal with the cross-border points of multiple clusters will make some cross-border points not belong to the best clustering. To solve this problem, an adjusting strategy after DBSCAN to change the positions of the points of every cluster's convex hull is proposed in this paper. At the end, the effectiveness of proposed adjustment strategy is verified by an experiment.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.ifacol.2022.05.038
- OA Status
- diamond
- Cited By
- 5
- References
- 9
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4285130320
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4285130320Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.ifacol.2022.05.038Digital Object Identifier
- Title
-
An Adjusting Strategy after DBSCANWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-01-01Full publication date if available
- Authors
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Runfa Zhang, Jianlong Qiu, Ming Guo, Huixia Cui, Xiangyong ChenList of authors in order
- Landing page
-
https://doi.org/10.1016/j.ifacol.2022.05.038Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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diamondOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1016/j.ifacol.2022.05.038Direct OA link when available
- Concepts
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DBSCAN, Cluster analysis, Convex hull, Computer science, Data mining, Cluster (spacecraft), Regular polygon, Data point, Pattern recognition (psychology), Artificial intelligence, Mathematics, Correlation clustering, CURE data clustering algorithm, Geometry, Programming languageTop concepts (fields/topics) attached by OpenAlex
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5Total citation count in OpenAlex
- Citations by year (recent)
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2024: 2, 2023: 2, 2022: 1Per-year citation counts (last 5 years)
- References (count)
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9Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.hull | 58 |
| abstract_inverted_index.make | 28 |
| abstract_inverted_index.some | 29 |
| abstract_inverted_index.this | 40, 62 |
| abstract_inverted_index.will | 27 |
| abstract_inverted_index.with | 20 |
| abstract_inverted_index.after | 45 |
| abstract_inverted_index.come, | 15 |
| abstract_inverted_index.every | 55 |
| abstract_inverted_index.first | 14, 16 |
| abstract_inverted_index.solve | 39 |
| abstract_inverted_index.DBSCAN | 0, 46 |
| abstract_inverted_index.belong | 33 |
| abstract_inverted_index.change | 48 |
| abstract_inverted_index.convex | 57 |
| abstract_inverted_index.paper. | 63 |
| abstract_inverted_index.points | 23, 31, 53 |
| abstract_inverted_index.served | 17 |
| abstract_inverted_index.mining. | 9 |
| abstract_inverted_index.popular | 3 |
| abstract_inverted_index.However, | 10 |
| abstract_inverted_index.clusters | 26 |
| abstract_inverted_index.multiple | 25 |
| abstract_inverted_index.problem, | 41 |
| abstract_inverted_index.proposed | 60, 70 |
| abstract_inverted_index.strategy | 44, 72 |
| abstract_inverted_index.verified | 74 |
| abstract_inverted_index.adjusting | 43 |
| abstract_inverted_index.algorithm | 6 |
| abstract_inverted_index.cluster's | 56 |
| abstract_inverted_index.positions | 50 |
| abstract_inverted_index.principle | 12 |
| abstract_inverted_index.adjustment | 71 |
| abstract_inverted_index.clustering | 5 |
| abstract_inverted_index.clustering. | 37 |
| abstract_inverted_index.experiment. | 77 |
| abstract_inverted_index.cross-border | 22, 30 |
| abstract_inverted_index.density-based | 4 |
| abstract_inverted_index.effectiveness | 68 |
| cited_by_percentile_year.max | 96 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5083193684, https://openalex.org/A5025032996, https://openalex.org/A5103109042 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| corresponding_institution_ids | https://openalex.org/I15823474, https://openalex.org/I202126657 |
| citation_normalized_percentile.value | 0.75235742 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |