Computer Science ›› 2016, Vol. 43 ›› Issue (Z11): 436-442.doi: 10.11896/j.issn.1002-137X.2016.11A.098

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UCNK-Means Clustering Method for Position Uncertain Data Based on Connection Number

WANG Jun and HUANG De-cai   

  • Online:2018-12-01 Published:2018-12-01

Abstract: Clustering for position uncertain data is a new problem of uncertain data clustering.Mainly there are two solutions to this new problem.The first is clustering acquiring the probability density function or probability distribution function of uncertain object and getting the expected distance with integral operation.The second is clustering by series of operation of interval data.However,the former has the disadvantages of getting probability density function hard,complex operation and poor practicability,and the latter ignores the effect of the range of interval data to the result of clustering.Therefore,a new uncertain data clustering method UCNK-Means was put forward.This method uses connection number as the model of uncertain object and defines connection distance between two objects and uses the situationvalue to compare the connection distance,which overcome the disadvantages existed in the two solutions above.The experiment illustrates that UCNK-Means has high precision of clustering,low complexity and strong praticability.

Key words: Uncertain data,Connection number,Clustering,Data mining

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