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PNMBG: Point Neighborhood Merging with Border Grids

Renxia Wan ; College of Information Science and Technology
Jingchao Chen ; College of Information Science and Technology
Lixin Wang ; College of Information Science and Technology
Xiaoke Su ; College of Information Science and Technology

Puni tekst: engleski, pdf (252 KB) str. 297-305 preuzimanja: 596* citiraj
APA 6th Edition
Wan, R., Chen, J., Wang, L. i Su, X. (2009). PNMBG: Point Neighborhood Merging with Border Grids. Journal of Information and Organizational Sciences, 33 (2), 297-305. Preuzeto s https://hrcak.srce.hr/45065
MLA 8th Edition
Wan, Renxia, et al. "PNMBG: Point Neighborhood Merging with Border Grids." Journal of Information and Organizational Sciences, vol. 33, br. 2, 2009, str. 297-305. https://hrcak.srce.hr/45065. Citirano 15.11.2019.
Chicago 17th Edition
Wan, Renxia, Jingchao Chen, Lixin Wang i Xiaoke Su. "PNMBG: Point Neighborhood Merging with Border Grids." Journal of Information and Organizational Sciences 33, br. 2 (2009): 297-305. https://hrcak.srce.hr/45065
Harvard
Wan, R., et al. (2009). 'PNMBG: Point Neighborhood Merging with Border Grids', Journal of Information and Organizational Sciences, 33(2), str. 297-305. Preuzeto s: https://hrcak.srce.hr/45065 (Datum pristupa: 15.11.2019.)
Vancouver
Wan R, Chen J, Wang L, Su X. PNMBG: Point Neighborhood Merging with Border Grids. Journal of Information and Organizational Sciences [Internet]. 2009 [pristupljeno 15.11.2019.];33(2):297-305. Dostupno na: https://hrcak.srce.hr/45065
IEEE
R. Wan, J. Chen, L. Wang i X. Su, "PNMBG: Point Neighborhood Merging with Border Grids", Journal of Information and Organizational Sciences, vol.33, br. 2, str. 297-305, 2009. [Online]. Dostupno na: https://hrcak.srce.hr/45065. [Citirano: 15.11.2019.]

Sažetak
The special clustering algorithm is attractive for the task of grouping arbitrary shaped database into several proper classes. Up to now, a wide variety of clustering algorithms designed for this task have been proposed, the majority of these algorithms is density-based. But the effectivity and efficiency still is the great challenges for these algorithms as far as the clustering quality of such task is concerned. In this paper, we propose an arbitrary shaped clustering method with border grids (PNMBG), PNMBG is a crisp partition method. It groups objects to point neighborhoods firstly, and then iteratively merges these point neighborhoods into clusters via grids, only bordering grids are considered during the merging stage. Experiments show that PNMBG has a good efficiency especially on the database with high dimension. In general, PNMBG outperforms DBSCAN in the term of efficiency and has an almost same effectivity with the later.

Ključne riječi
Clustering; Grid clique; Point neighborhood; Border grids; Merging

Hrčak ID: 45065

URI
https://hrcak.srce.hr/45065

Posjeta: 699 *