Mongolian Similar Elements Clustering via Immune Clone Algorithm
Received:August 24, 2019  Revised:October 12, 2019
Key Word: immune clone algorithm   Mongolian similar elements clustering   K-means  
Fund ProjectL:Supported by the Project of Inner Mongolia University for Nationalities (Grant No.NMDYB18009), the National Natural Science Foundation of China (Grant No.61473328; 11401076) and the Fundamental Research Funds for the Central Universities (Grant No.DUT18JC02).
Author NameAffiliation
Chunhua School of Mathematical Sciences, Dalian University of Technology, Liaoning 116024, P. R. China
College of Computer Sciences and Technology, Inner Mongolia University for Nationalities, Inner Mongolia 028043, P. R. China 
Chao ZHANG School of Mathematical Sciences, Dalian University of Technology, Liaoning 116024, P. R. China 
Yan LIU Department of General Education, Dalian Polytechnic University, Liaoning 116034, P. R. China 
Wei WU School of Mathematical Sciences, Dalian University of Technology, Liaoning 116024, P. R. China 
Hits: 37
Download times: 41
Abstract:
      Text clustering is an important research issue of clustering technique. It aims to use the similar characteristics or similar expression to group the text so that the texts in the same clusters have the greatest similarity, and those in different clusters have the greatest dissimilarity. There are many characteristics in Mongolian structure and writing-mode compared with other kinds of characters. By combining K-means and clone immune algorithm, we propose a novel clustering technique called ICKM. Numerical experiments on four elements sets illustrate the validity of our method in the clustering task for Mongolian.
Citation:
DOI:10.3770/j.issn:2095-2651.2019.06.017
View Full Text  View/Add Comment  Download reader