Web User’s Access Pattern Identification Using Clustering Algorithms: A Survey
Prerna Kumari, Aneesh Kumar Mishra, Rahul Kumar
Abstract
Prerna Kumari, Aneesh Kumar Mishra, Rahul Kumar
Abstract
Users of web site usually perform their interest oriented actions by clicking or visiting web pages, which are traced in access log files. The clustering web client's access pattern may catch common client interest in a website. The conventional web usage mining techniques for clustering web user sessions can discover usage patterns directly, but cannot identify the latent factors or hidden relationships among users' navigational behaviour. One of the best tasks of internet usage mining, web client grouping, which sets up clusters of clients displaying comparative browsing designs gives beneficial information to customized web benefits. This paper presents a survey covering the strategies and techniques of clustering algorithms and demanding situations appear within the area.
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Users of web site usually perform their interest oriented actions by clicking or visiting web pages, which are traced in access log files. The clustering web client's access pattern may catch common client interest in a website. The conventional web usage mining techniques for clustering web user sessions can discover usage patterns directly, but cannot identify the latent factors or hidden relationships among users' navigational behaviour. One of the best tasks of internet usage mining, web client grouping, which sets up clusters of clients displaying comparative browsing designs gives beneficial information to customized web benefits. This paper presents a survey covering the strategies and techniques of clustering algorithms and demanding situations appear within the area.
Key concepts: Computer science, Web mining, Cluster analysis, World Wide Web, Web navigation, Web page, Web modeling, Data Web