期刊名称:International Journal of Advanced Research In Computer Science and Software Engineering
印刷版ISSN:2277-6451
电子版ISSN:2277-128X
出版年度:2012
卷号:2
期号:12
出版社:S.S. Mishra
摘要:World Wide Web provides abundance of information for the Internet users and is a huge repository of web pages and links. The growth of web is tremendous as approximately one million pages are added daily. Web logs record users' accesses. Because of the tremendous usage of web , the web log files are growing at a faster rate and the size is becoming huge. Web data mining is the application of data mining techniques in web data. Web Usage Mining applies mining techniques in log data to extract the behaviour of users which is used in various applications like personalized services, adaptive web sites, customer profiling, prefetching, creating attractive web sites etc., and consists of three phases preprocessing, pattern discovery and pattern analysis. Web log data is usually noisy and ambiguous and preprocessing is an important process before mining. To characterize users access pattern, the navigation patterns identified are expected to capture the user's interests and also be used as a prediction system. The experimental results performed on rea l usage data from a commercial web site show a significant improvement in the pattern identification.
关键词:Classification; Clustering; Prediction; Recommendations; Web Usage Mining