Journal of Computer Applications ›› 2019, Vol. 39 ›› Issue (7): 1869-1882.DOI: 10.11772/j.issn.1001-9081.2019010174

• Artificial intelligence •     Next Articles

Review of clustering algorithms

ZHANG Yonglai, ZHOU Yaojian   

  1. Software School, North University of China, Taiyuan Shanxi 030051, China
  • Received:2019-01-23 Revised:2019-04-09 Online:2019-04-15 Published:2019-07-10
  • Supported by:

    This work is partially supported by the National Natural Science Foundation of China (6160051296).


章永来, 周耀鉴   

  1. 中北大学 软件学院, 太原 030051
  • 通讯作者: 周耀鉴
  • 作者简介:章永来(1978-),男,浙江诸暨人,助理教授,博士,主要研究方向:大数据分析与处理、医疗大数据、海洋大数据;周耀鉴(1987-),男,湖北武穴人,助理教授,博士,主要研究方向:大数据分析与处理、海洋大数据、水下机器人。
  • 基金资助:



Clustering is very important as an unsupervised learning algorithm in the age of big data. Recently, considerable progress has been made in the analysis of clustering algorithm. Firstly, the whole process of clustering, similarity measurement, new classification of clustering algorithms and evaluation on their results were summarized. Clustering algorithms were divided into two categories:big data clustering and small data clustering, and the systematic analysis and summary of big data clustering were carried out particularly. Moreover, the research progress and application of various clustering algorithms were summarized and analyzed, and the development trend of clustering algorithms was discussed in combination with the research topics.

Key words: clustering, similarity measurement, big data clustering, small data clustering, clustering evaluation



关键词: 聚类, 相似性度量, 大数据聚类, 小数据聚类, 聚类评价

CLC Number: