Effective Clustering Algorithm for Probabilistic Data Stream

2010 ◽  
Vol 20 (5) ◽  
pp. 1313-1328 ◽  
Author(s):  
Dong-Bo DAI ◽  
Gang ZHAO ◽  
Sheng-Li SUN
Keyword(s):  
Data Stream ◽  
Clustering Algorithm ◽  
Probabilistic Data

Queries for Uncertain Data on Dataspace Based on Effective Clustering Algorithm

2013 ◽  
Vol 380-384 ◽  
pp. 1529-1532
Author(s):  
Shuang Zhang ◽  
Shi Xiong Zhang
Keyword(s):  
Data Stream ◽  
Clustering Algorithm ◽  
Uncertain Data ◽  
Effective Strategy ◽  
Clustering Method ◽  
Probabilistic Data ◽  
Stream Clustering ◽  
Data Stream Clustering ◽  
Strong Cluster ◽  
First Time

This paper presents a probabilistic data stream clustering method P-Stream. An effective clustering algorithm called P-Stream for probabilistic data stream is developed in this paper for the first time. For the uncertain tuples in the data stream, the concepts of strong cluster, transitional clusters and weak cluster are proposed in the P-Stream. With these concepts, an effective strategy of choosing candidate cluster is designed, which can find the sound cluster for every continuously arriving data point. In this paper, we systematically defined the dataspace, the uncertain data, and proposed a updated algorithm of queries on uncertain data based on Effective Clustering Algorithm.

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