Frequent Itemset Creation using Sequence Association Rule

J.-C. Yun and S.-D. Youn (Korea)


Association Rule, Sequence pattern, Web Mining


The volume of transaction on the website e-Commerce has demonstrated explosive annual growth. According to studies, this is due to customer's access to merchandise information, establishment of marketing strategy, and ensuring analysis of customer purchases are progressing. To further understand the buying pattern of customers at E-Commerce, analyses are performed using the direct interviews and monitoring of customers. The most widely utilized tool is the web log files. These provide the most objective observations of customers who use the website. To determine the patterns of web-use among customers, many techniques of web mining are being studied. The movements of visitors to web sites are recorded and logged as data. Analyses based on this data provides important information for designing personalized user-oriented pages. We reviews the methods employed to design a website which is more personalized to the customers through the adoption of the sequence Association Rule. It will perform an analysis of the procedural step to web- use mining and movement patterns within the basis of web log data.

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