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Cluster Computing

, Volume 21, Issue 1, pp 945–953 | Cite as

Clustering based on words distances

  • Hongtao Liu
  • Hongwei GuanEmail author
  • Jie Jian
  • Xueyan Liu
  • Ying Pei
Article
  • 129 Downloads

Abstract

In order to find the relevance of the key words in the hot topics effectively, we proposed a clustering method based on words-distances. We calculated the distances between the words firstly, then calculated the sectional density of each words. We regarded the words which have higher sectional density and far away from sectional density point as the center point in the clustering. After find the center point, we start to clustering. This method through decision diagram on estimating the number of clusters. At last, we can find the results on the evaluating indicator of accuracy rate and recall rate.

Keywords

Hot topic Clustering Accuracy rate Recall rate 

Notes

Acknowledgements

This research is supported by the following fundings or programs: the National Natural Science Foundation of China (61402309), the Fundamental Research Funds for the Central Universities (No. XDJK2014B012), the National Social Science Foundation of China (13CGL146), the National Social Science Foundation of China (15BGL2729), the Study on the Key Common Characteristics of Network Transaction Fraud (14SKF01).

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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Hongtao Liu
    • 1
  • Hongwei Guan
    • 1
    Email author
  • Jie Jian
    • 2
  • Xueyan Liu
    • 2
  • Ying Pei
    • 2
  1. 1.College of Computer Science and TechnologyChongqing University of Posts and TelecommunicationsChongqingChina
  2. 2.School of Economics and ManagementChongqing University of Posts and TelecommunicationsChongqingChina

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