2024-03-28T10:47:19Z
https://meral.edu.mm/oai
oai:meral.edu.mm:recid/4466
2022-03-24T23:12:16Z
1582963302567:1597824273898
user-ucsy
Analysis of Web User Clustering based on Users’ Access Behavior
Shwe, Theint Theint
World Wide Web overwhelms us with theimmense amounts of widely distributedinterconnected, rich and dynamicinformation. Provision of services to userscorrectly according to their needs is one ofthe most important issues in Web. However,provision of services to individual users’need is time consuming and overburden forthe web site developers or administrator.Not only for the developers but also for theusers, group-based service provision canfulfill this situation at the same time. In thispaper, clustering algorithms: SelfOrganizing Map (SOM) and K-Means areused to analyze the users’ access behavior.The correctness of the clustering algorithmsis tested with two external validationindexes. Our implementation results showthat SOM gives better results than K-Means.
2012-02-28
http://hdl.handle.net/20.500.12678/0000004466
https://meral.edu.mm/records/4466