Title :
A Web Users Clustering Model Based on Users´ Browsing Path
Author :
Ding Xiaoming ; Ma Xiaoyan
Author_Institution :
Coll. of Comput. & Inf. Sci., Southwest Univ., Chongqing, China
Abstract :
Based on user´s browsing path, a novel clustering model is proposed to cluster Web users. It represents users´ characteristics by their transaction paths and presents a new similarity computational method-WUSC (Web user similarity calculation). Considering the relationship between the common path and the whole path of the user, combining with the residence time of user´s paths to calculate the similarity between users, the user´s transaction paths are represented as sequential patterns,. The experiment results prove the efficiency of the proposed method.
Keywords :
Internet; data mining; pattern clustering; Web user clustering model; Web user similarity calculation; user browsing path; Clustering algorithms; Educational institutions; Frequency; History; Information science; Navigation; Partitioning algorithms; Robustness; Uniform resource locators;
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.2009.5364758
