K-DBSCAN: Identifying Spatial Clusters with Differing Density Levels-Reference-Cited by-同舟云学术

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K-DBSCAN: Identifying Spatial Clusters with Differing Density Levels

Published:2015-09 Issue: Volume: Page:
ISSN:
Container-title:2015 International Workshop on Data Mining with Industrial Applications (DMIA)
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Author:

Debnath Madhuri,Tripathi Praveen Kumar,Elmasri Ramez

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/7528193/7544953/07544972.pdf?arnumber=7544972

Cited by 18 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A scalable multi-density clustering approach to detect city hotspots in a smart city;Future Generation Computer Systems;2024-08

2. An Improved Density Peaks Clustering Algorithm Based On Density Ratio;The Computer Journal;2024-03-02

3. MPCD: An Algorithm for Discovering Multilevel Prevalent Co-location Patterns from Heterogeneous Distribution of Spatial Datasets;Lecture Notes in Computer Science;2024

4. Hybrid Density- Grid Based Clustering Algorithms: A Review;2023 7th International Conference On Computing, Communication, Control And Automation (ICCUBEA);2023-08-18

5. Taxonomy of outlier detection methods for power system measurements;Energy Conversion and Economics;2023-04

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