Title :
Research of Web Transactions Clustering Analysis Based on Ant-Colony Algorithm
Author :
Kejun Zhang ; Rong Qian ; Xiaokun Zhang ; Zhixiang Zhu ; Geng Zhao
Author_Institution :
Dept. of Comput. Sci. & Technol., Beijing Electron. Sci. & Technol. Inst., Beijing, China
Abstract :
This paper discusses the two important phases, which are data preprocessing and clustering analysis, in Web transactions clustering analysis, in order to gain an easily interpreted clustering result, we introduce the "Concept URL" in the data preprocessing phase; In the clustering analysis phase, A model of artificial ant is set up. Based on this model, we implement an ant-colony clustering algorithm. What\´s more, k-means algorithm is also implemented in the phase, the result is compared with that of ant colony algorithm. Experiment results show that the algorithm is valid, it can effectively and accurately gain Web transactions clustering patterns.
Keywords :
Internet; optimisation; pattern clustering; transaction processing; Concept URL; Web transactions clustering analysis; Web transactions clustering patterns; ant-colony algorithm; ant-colony clustering algorithm; artificial ant; clustering analysis phase; data preprocessing; k-means algorithm; Algorithm design and analysis; Clustering algorithms; Computer science; Data mining; Data preprocessing; File servers; Information analysis; Partitioning algorithms; Pattern analysis; Web mining;
Conference_Titel :
Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4507-3
Electronic_ISBN :
978-1-4244-4507-3
DOI :
10.1109/CISE.2009.5363034
