Dissertation > Excellent graduate degree dissertation topics show

Research on Data Stream Clustering Algorithm Based on Sliding Windows and Subspace Partition

Author: WangHao
Tutor: ZhangZhongPing
School: Yanshan University
Course: Applied Computer Technology
Keywords: Data mining Data stream Clustering Sliding window CD-Tree grid
CLC: TP311.13
Type: Master's thesis
Year: 2010
Downloads: 159
Quote: 0
Read: Download Dissertation

Abstract


Recently, with the rapid development of communication technology and netwok technology, a new model of data-data stream has come into being. This new model data has many real applications, such as Web clicking stream, telecommucation, weather predication, stock exchange information. The main differences between traditional database and data stream are: (1) data stream is unbounded and can not be stored completely; (2) data are transmitted rapidly and changed timely; (3) data arrivel are continuously and orderly; (4) the objects can be read once or several times.According to the characteristics of data stream, cluster analysis becomes hot studying problem in data mining. Many clustering methods have been proposed recently, and got some achievements. According to the characteristics of data stream, this paper mainly researches on clustering algorithms over data streams.Firstly, research on clustering method over dynamical sliding window. In order to address the data streams with varying speed, we propose an efficient data streams clustering algorithm over dynamic sliding windows, which based on the two-phased framework. In the online component, the novel micro-cluster feature is introduced to store the important statistical information of data streams. Through computing the distances from data points to the center of each micro-cluster, and adjusting the sizes of sliding windows, the corresponding clustering features are maintained dynamically. In the offline component, by employing the mean values of the micro-clusters in online component, we adopts k-means algorithm to generate the final clustering results. Experimental results show that our approach has higher clustering purity and better scalability.Secondly, research on clustering high dimensional data stream based on subspace partition. We propose a fast subspace partition data streams clustering algorithm, which adopts two-phased clustering framework. In the online component, the extension of adjacent unit (E-unit), which has common edge or vertex with dense units, is presented. Moreover, the improved CD-Tree lattice structure is introduced to store the information of non-empty units, maintain the position relationships among units, and keep the affiliation between dense units (D-unit) and E-units. Outdated units which need to be faded are performed by decayed function, so that the corresponding micro-clusters are maintained dynamically. In the offline component, the final clusters are generated according to all the micro-clusters by searching D-units in radius range.Lastly, implement the above two algorithms with language of JAVA. All of our experiments are performed on the real life dataset KDD-CUP-99 and synthetic dataset to execute the algorithms this paper presented. The experimental results show the feasibility and effectiveness of our algorithms.

Related Dissertations

  1. Research and Implementation of Mining Implicit User Interest,TP311.13
  2. Establishment and Update of Similar Users’ Cluster in Personalized Information Retrieval,TP391.3
  3. Research on Removal Algorithm of Shadows in Image Segmentation,TP391.41
  4. A Study on Healthcare Product Marketing Based on Data Mining Technology,F426.72
  5. Gao Zhong-ying academic thought and experience and use of Bufei Decoction treatment of common diseases of the respiratory system drug law,R249.2
  6. Bing- thick academic thought and clinical experience and empirical studies apply to turtle soups treatment of chronic kidney disease,R249.2
  7. Research and Improvement on K-Means Clustering Algorithm,TP311.13
  8. Research on Peer-to-Peer Traffic Identification Algorithm Based on Cluster Analysis,TP393.02
  9. Research of Scheduling Algorithm Based on Hybrid Adaptive Genetic Algorithm in Computing Grid,TP393.09
  10. Evaluation of Photosynthetic Efficiancy of Seedlings of the Hybrid Progenies （F1） in Peach,S662.1
  11. The Load Research and Comprehensive Evaluation on the Agricultural Non-Point Source Pollution in Nantong,X592
  12. The Design and Implementation of Bicluster Data Analyzing Software,TP311.52
  13. BF-FCM Clustering Algorithm and Its Application in the Image Segmentation,TP391.41
  14. Research on Clustering Algorithm Based on Mutation Particle Swarm Optimization,TP18
  15. Research on K-means Optimization Clustering Algorithm,TP311.13
  16. Research on Fuzzy C-Mean Clustering Algorithm Based on Particle Swarm Optimization and Shuffled Frog Leaping Algorithm,TP18
  17. Research on Clustering Algorithm Based on Genetic Algorithm and Rough Set Theory,TP18
  18. Study on Photosynthetic Characteristics of Peach Based on Heterosis of Assimilation Capacity,S662.1
  19. Evolutionary Clustering Algorithm and Its Application,TP311.13
  20. Vehicle detection based on machine vision and vehicle distance measuring method,TP274
  21. Based on data mining research tax audit case selection,F812.42

CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer software > Program design,software engineering > Programming > Database theory and systems
© 2012 www.DissertationTopic.Net  Mobile