Journal of Shandong University(Engineering Science) ›› 2022, Vol. 52 ›› Issue (2): 118-127.doi: 10.6040/j.issn.1672-3961.0.2021.310

Previous Articles    

A clustering algorithm based on dynamic local density and cluster structure

LU Jianyun1,2, ZHANG Wei3, LI Lin2   

  1. 1. School of Artificial Intelligence and Big Data, Chongqing College of Electronic Engineering, Chongqing 401331, China;
    2. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, Sichuan, China;
    3. The 29th Research Institute, China Electronics Technology Group Corporation, Chengdu 610036, Sichuan, China
  • Published:2022-04-20

CLC Number: 

  • TP391
[1] 章永来, 周耀鉴.聚类算法综述[J].计算机应用, 2019, 39(7):1869-1882. ZHANG Yonglai, ZHOU Yaojian. Review ofclustering algorithms[J].Journal of Computer Applications, 2019, 39(7):1869-1882.
[2] UTTARKABAT S, SUNKARA N D, PATRA B K. RSOD: efficient technique for outlier detection using reverse nearest neighbors statistics[C] //Proceedings of the 4th International Conference on Computational Intel-ligence and Networks(CINE).Kolkata, India:IEEE, 2020:1-6.
[3] KURSUN O. Spectral clustering with reverse soft k-nearest neighbor density estimation[C] // Proceedings of the 2010 International Joint Conference on Neural Networks(IJCNN). Barcelona, Spain: IEEE, 2010: 1-8.
[4] BRYANT A, COIL K. RNN-DBSCAN: a density-based clustering algorithm using reverse nearest neighbor density estimates[J].IEEE Transactions on Knowledge and Data Engineering, 2018, 30(6):1109-1121.
[5] VADAPALLI S, VALLURI S R, KARLAPALEM K. A simple yet effective data clustering algorithm[C] //Proceedings of the Sixth International Conference on Data Mining(ICDM’06). Hong Kong, China: IEEE, 2006:1108-1112.
[6] WU Q, ZHANG Q, SUN R, et al. Adaptive density peak clustering based on dimensional-free and reverse k-nearest neighbors[J]. Information Technology and Control, 2020, 49(3):395-411.
[7] LIU Y, LIU D, YU F, et al. A double-density clustering method based on "nearest to first in" strategy[J]. Symmetry-Basel, 2020, 12(5):747-764.
[8] LU J, ZHU Q. An Effective algorithm based on density clustering framework[J]. IEEE Access, 2017:4991-5000.
[9] MUTHUKRISHNAN S. Influence sets based on reverse nearest neighbor queries[C] //Proceedings of the International Conference on Management of Data.Dallas, United States: ACM, 2000:201-212.
[10] ESTER M, KRIEGEL H P, SANDER J, et al. A density-based algorithm for discovering clusters in large spatial databases with noise[C] // Proceedings of the 2nd International Conference on Knowledge Discovery(KDD).Portland, United States:AAAI press, 1996:226-231.
[11] SCITO VS KI R, SABO K. DBSCAN-like clustering method for various data densities[J].Pattern Analysis and Applications, 2020, 23(2):541-554.
[12] CHEN Y, ZHOU L, BOUGUILA N, et al. BLOCK-DBSCAN: fast clustering for large scale data[J].Pattern Recognition, 2021, 51(6):3939-3953.
[13] ANKERST M, BREUNIG M, KRIEGELH P, et al. OPTICS: ordering points to identify the clustering structure[C] //Proceedings of the International Conference on Management of Data. Nanjing, China: ACM, 1999:49-60.
[14] RODRIGUEZ A, LAIO A. Clustering by fast search and find of density peaks[J]. Science, 2014, 344(6191):1492-1496.
[15] 刘颖莹,刘培玉,王智昊,等.一种基于密度峰值发现的文本聚类算法[J].山东大学学报(理学版), 2016, 51(1):65-70. LIU Yingying, LIU Peiyu, WANG Zhihao, et al. A text clustering algorithm based on find of density peaks [J].Journal of Shandong University(Natural Science), 2016, 51(1):65-70.
[16] DIAO Q, DAI Y, AN Q, et al. Clustering by detecting density peaks and assigning points by similarity-first search based on weighted k-nearest neighbors graph[J]. Complexity, 2020:1-17.
[17] ABBAS M, EL-ZOGHABI A, SHOUKRY A. DenMune: density peak based clustering using mutual nearest neighbors[J]. Pattern Recognition, 2020:1-18.
[18] 杨天鹏,徐鲲鹏,陈黎飞.非均匀数据的变异系数聚类算法[J].山东大学学报(工学版), 2018,48(3):140-146. YANG Tianpeng, XU Kunpeng, CHEN Lifei. Coef-ficient of variation clustering algorithm for non-uniform data[J]. Journal of Shandong University(Engineering Science), 2018, 48(3):140-146.
[19] 卢建云,朱庆生,吴全旺.一种启发式确定聚类数方法[J].小型微型计算机系统, 2018, 39(7):1381-1385. LU Jinayun, ZHU Qingsheng, WU Quanwang. Heuristic method of determining the number of clusters[J]. Journal of Chinese Computer Systems, 2018, 39(7):1381-1385.
[20] 纪霞,姚晟,赵鹏.相对邻域与剪枝策略优化的密度峰值聚类算法[J].自动化学报,2020,46(3):562-575. JI Xia, YAO Cheng, ZHAO Peng. Relative neigh-borhood and pruning strategy optimized density peaks clustering algorithm [J].Acta Automatica Sinica, 2020, 46(3):562-575.
[21] BAKOUCH H, KACHOUR M, NADARAJAH S. An extended Poisson distribution[J]. Communications in Statistics-Thoeryand Methods, 2013, 45(22):6746-6764.
[22] University of Eastern Finland. Clustering datasets: Shape sets[DB/OL].[2022-02]. https://cs.joensuu.fi/sipu/datasets/.
[23] LICHMAN M. UCI machine learning repository 2013. [DB/OL]. [2022-02]. http://archive.ics.uci.edu/ml.
[24] LIU X, CHENG H M, ZHANG Z Y, Evaluation of community detection methods[J].IEEE Transactions on Knowledge and Data Engineering, 2020, 32(9):1736-1746.
[1] Tongyu JIANG,Fan CHEN,Hongjie HE. Lightweight face super-resolution network based on asymmetric U-pyramid reconstruction [J]. Journal of Shandong University(Engineering Science), 2022, 52(1): 1-8, 18.
[2] Jun HU,Dongmei YANG,Li LIU,Fujin ZHONG. Cross social network user alignment via fusing node state information [J]. Journal of Shandong University(Engineering Science), 2021, 51(6): 49-58.
[3] Ye LIANG,Nan MA,Hongzhe LIU. Image-dependent fusion method for saliency maps [J]. Journal of Shandong University(Engineering Science), 2021, 51(4): 1-7.
[4] Xinlu ZONG,Jiayuan DU. Evacuation simulation model based on multi-target driven artificial bee colony algorithm [J]. Journal of Shandong University(Engineering Science), 2021, 51(3): 1-6.
[5] YANG Xiuyuan, PENG Tao, YANG Liang, LIN Hongfei. Adaptive multi-domain sentiment analysis based on knowledge distillation [J]. Journal of Shandong University(Engineering Science), 2021, 51(3): 15-21.
[6] FU Guixia, ZOU Guofeng, MAO Shuai, PAN Jinfeng, YIN Liju. Small sample person re-identification combining Gabor features and convolution features [J]. Journal of Shandong University(Engineering Science), 2021, 51(3): 22-29.
[7] TAO Liang, LIU Baoning, LIANG Wei. Automatic detection research of arrhythmia based on CNN-LSTM hybrid model [J]. Journal of Shandong University(Engineering Science), 2021, 51(3): 30-36.
[8] Junsan ZHANG,Qiaoqiao CHENG,Yao WAN,Jie ZHU,Shidong ZHANG. MIRGAN: a medical image report generation model based on GAN [J]. Journal of Shandong University(Engineering Science), 2021, 51(2): 9-18.
[9] Fengyu ZHOU,Panlong GU,Fang WAN,Lei YIN,Jiakai HE. Overview of multi-motion vision odometer [J]. Journal of Shandong University(Engineering Science), 2021, 51(1): 1-10.
[10] WANG Mei, XUE Chenglong, ZHANG Qiang. Multi-kernel combination method based on rank spatial difference [J]. Journal of Shandong University(Engineering Science), 2021, 51(1): 108-113.
[11] Xiaolan XIE,Qi WANG. A scheduling algorithm based on multi-objective container cloud task [J]. Journal of Shandong University(Engineering Science), 2020, 50(4): 14-21.
[12] Guoyong CAI,Xinhao HE,Yangyang CHU. Visual sentiment analysis based on spatial attention mechanism and convolutional neural network [J]. Journal of Shandong University(Engineering Science), 2020, 50(4): 8-13.
[13] Keyang CHENG,Shuang SUN,Yongzhao ZHAN. Modified SuBSENSE algorithm via adaptive distance threshold based on background complexity [J]. Journal of Shandong University(Engineering Science), 2020, 50(3): 38-44.
[14] Feng TIAN,Xin LI,Fang LIU,Chuang LI,Xiaoqiang SUN,Ruishan DU. A semantictag generation method based on multi-model subspace learning [J]. Journal of Shandong University(Engineering Science), 2020, 50(3): 31-37, 44.
[15] Jinping MA. A multi-microcontroller communication method based on UART asynchronous serial communication protocol [J]. Journal of Shandong University(Engineering Science), 2020, 50(3): 24-30.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!