Path-scan: A novel clustering algorithm based on core points and connexity
作者:
Highlights:
• The clustering algorithm is oriented for a discovery task
• Clusters are characterized by several core and support patterns
• They can be path-connected via a density differential approach
• The Dijkstra algorithm is applied to produce the optimal path
• Performance is assessed using synthetic and real-world data
摘要
•The clustering algorithm is oriented for a discovery task•Clusters are characterized by several core and support patterns•They can be path-connected via a density differential approach•The Dijkstra algorithm is applied to produce the optimal path•Performance is assessed using synthetic and real-world data
论文关键词:Clustering,Natural cluster,Distance,Density,Neighbors
论文评审过程:Received 24 June 2021, Revised 12 July 2022, Accepted 27 July 2022, Available online 6 August 2022, Version of Record 12 August 2022.
论文官网地址:https://doi.org/10.1016/j.eswa.2022.118316