Abstract :
Understanding the navigational behaviour of website visitors is a significant factor of success in the emerging business model of electronic commerce and even mobile Commerce. The Web navigation patterns, termed throughout-surfing patterns (TSPs) as defined in this paper, are a superset of Web traversal patterns that effectively display the trends toward the next visited Web pages in a browsing session. TSPs are more expressive for understanding the purposes of website visitors. In this report, we first introduce the concept of throughout-surfing patterns and then present an efficient method for mining the patterns. We propose a compact graph structure, termed a path traversal graph, to record information about the navigation paths of website visitors. The graph contains the frequent surfing paths that are required for mining TSPs. In addition, we devised a graph traverse algorithm based on the proposed graph structure to discover the TSPs. This website will be hosted in a server, where we will be introducing the concept of automatic reconfiguration of storage systems. This system will be providing a master slave server where even if the master server crashes the replica of the data will be stored in the slave server dynamically and the slave server will be automatically configured as the master server. In this case the end user doesn´t have to face issues with server crash, data loss, or delay of data.
Keywords :
Internet; data mining; information retrieval; pattern classification; TSP; Web browsing session; Web navigation pattern; Web site visitors navigational behaviour; Web traversal pattern; automatic server reconfiguration; electronic commerce; master slave server; mobile commerce; pattern mining; storage system reconfiguration; throughout-surfing patterns; traversal graph; Computer crashes; Navigation; Servers; Master Server; Slave Server; TSPs (Throughout Surfing Patterns); dbQs;
