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An Optimization Model for Clustering Categorical Data Streams with Drifting Concepts

文献类型：期刊论文

作者Bai, Liang1,2; Cheng, Xueqi2; Liang, Jiye1; Shen, Huawei2
刊名IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
出版日期2016-11-01
卷号28期号:11页码:2871-2883
关键词Cluster analysis optimization model iterative algorithm categorical data stream drifting-concept detection
ISSN号1041-4347
DOI10.1109/TKDE.2016.2594068
英文摘要There is always a lack of a cluster validity function and optimization strategy to find out clusters and catch the evolution trend of cluster structures on a categorical data stream. Therefore, this paper presents an optimization model for clustering categorical data streams. In the model, a cluster validity function is proposed as the objective function to evaluate the effectiveness of the clustering model while each new input data subset is flowing. It simultaneously considers the certainty of the clustering model and the continuity with the last clustering model in the clustering process. An iterative optimization algorithm is proposed to solve an optimal solution of the objective function with some constraints. Furthermore, we strictly derive a detection index for drifting concepts from the optimization model. We propose a detection method that integrates the detection index and the optimization model to catch the evolution trend of cluster structures on a categorical data stream. The new method can effectively avoid ignoring the effect of the clustering validity on the detection result. Finally, using the experimental studies on several real data sets, we illustrate the effectiveness of the proposed algorithm in clustering categorical data streams, compared with existing data-streams clustering algorithms.
资助项目National Natural Science Foundation of China[61305073] ; National Natural Science Foundation of China[61432011] ; National Natural Science Foundation of China[61472400] ; National Natural Science Foundation of China[61573229] ; National Natural Science Foundation of China[U1435212] ; National Key Basic Research and Development Program of China (973)[2013CB329404] ; National Key Basic Research and Development Program of China (973)[2014CB340400] ; Foundation of Doctoral Program Research of Ministry of Education of China[20131401120001] ; Technology Research Development Projects of Shanxi[2015021100] ; Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi[2014104] ; Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi[2015107]
WOS研究方向Computer Science ; Engineering
语种英语
WOS记录号WOS:000385702000004
出版者IEEE COMPUTER SOC
源URL[http://119.78.100.204/handle/2XEOYT63/8003]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Bai, Liang
作者单位1.Shanxi Univ, Sch Comp & Informat Technol, Taiyuan 030006, Shanxi, Peoples R China
2.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Bai, Liang,Cheng, Xueqi,Liang, Jiye,et al. An Optimization Model for Clustering Categorical Data Streams with Drifting Concepts[J]. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING,2016,28(11):2871-2883.
APA Bai, Liang,Cheng, Xueqi,Liang, Jiye,&Shen, Huawei.(2016).An Optimization Model for Clustering Categorical Data Streams with Drifting Concepts.IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING,28(11),2871-2883.
MLA Bai, Liang,et al."An Optimization Model for Clustering Categorical Data Streams with Drifting Concepts".IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 28.11(2016):2871-2883.

入库方式： OAI收割

来源：计算技术研究所

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