hrcak mascot   Srce   HID

Izvorni znanstveni članak
https://doi.org/10.17559/TV-20180504150204

Gravity Theory-Based Affinity Propagation Clustering Algorithm and Its Applications

Limin Wang ; School of Management Science and Information Engineering, Jilin University of Finance and Economics, Jilin Big Data Research Center for Business, Changchun, 130117, China
Zhiyuan Hao ; School of Management Science and Information Engineering, Jilin University of Finance and Economics, Jilin Big Data Research Center for Business, Changchun, 130117, China
Xuming Han ; School of Computer Science and Engineering, Changchun University of Technology, Changchun, 130117, China
Ruihong Zhou ; School of Management Science and Information Engineering, Jilin University of Finance and Economics, Jilin Big Data Research Center for Business, Changchun, 130117, China

Puni tekst: engleski, pdf (2 MB) str. 1125-1135 preuzimanja: 195* citiraj
APA 6th Edition
Wang, L., Hao, Z., Han, X. i Zhou, R. (2018). Gravity Theory-Based Affinity Propagation Clustering Algorithm and Its Applications. Tehnički vjesnik, 25 (4), 1125-1135. https://doi.org/10.17559/TV-20180504150204
MLA 8th Edition
Wang, Limin, et al. "Gravity Theory-Based Affinity Propagation Clustering Algorithm and Its Applications." Tehnički vjesnik, vol. 25, br. 4, 2018, str. 1125-1135. https://doi.org/10.17559/TV-20180504150204. Citirano 12.11.2019.
Chicago 17th Edition
Wang, Limin, Zhiyuan Hao, Xuming Han i Ruihong Zhou. "Gravity Theory-Based Affinity Propagation Clustering Algorithm and Its Applications." Tehnički vjesnik 25, br. 4 (2018): 1125-1135. https://doi.org/10.17559/TV-20180504150204
Harvard
Wang, L., et al. (2018). 'Gravity Theory-Based Affinity Propagation Clustering Algorithm and Its Applications', Tehnički vjesnik, 25(4), str. 1125-1135. https://doi.org/10.17559/TV-20180504150204
Vancouver
Wang L, Hao Z, Han X, Zhou R. Gravity Theory-Based Affinity Propagation Clustering Algorithm and Its Applications. Tehnički vjesnik [Internet]. 2018 [pristupljeno 12.11.2019.];25(4):1125-1135. https://doi.org/10.17559/TV-20180504150204
IEEE
L. Wang, Z. Hao, X. Han i R. Zhou, "Gravity Theory-Based Affinity Propagation Clustering Algorithm and Its Applications", Tehnički vjesnik, vol.25, br. 4, str. 1125-1135, 2018. [Online]. https://doi.org/10.17559/TV-20180504150204

Sažetak
The original Affinity Propagation clustering algorithm (AP) only used the Euclidean distance of data sample as the only standard for similarity calculation. This method of calculation had great limitations for data with high dimension and sparsity when the original algorithm was running. Due to the single calculation method of similarity, the convergence and clustering accuracy of the algorithm were greatly affected. On the other hand, in the universe, we can consider the formation of galaxies is a clustering process. In addition, the interaction between different celestial bodies are achieved through universal gravitation. This paper introduced the Density Peak clustering algorithm (DP) and gravitational thought into the AP algorithm, and constructed the density property to calculate the similarity, put forward the Affinity Propagation clustering algorithm based on Gravity (GAP). The proposed algorithm was more accurate to calculate similarity of simple points through the local density of corresponding points, and then used the gravity formula to update the similarity matrix. The data clustering process could be seen as the sample points spontaneously attract each other based on ‘gravitation’. Experimental results showed that the convergence performance of GAP algorithm is obviously improved over the AP algorithm, and the clustering effect was better.

Ključne riječi
affinity propagation algorithm; gravitation theory; local density; similarity matrix

Hrčak ID: 204462

URI
https://hrcak.srce.hr/204462

Posjeta: 320 *