In recent years, there is a tremendous growth of web applications in various fields. People are using World Wide Web for different needs such as to retrieve information for e-commerce, e-governance and many more. Day by Day information available on World Wide Web is increasing exponentially, it becomes much more difficult for web users to access relevant information efficiently. Hence, it is required to develop a good recommendation system which can used to reduce the workload of web users. Usually, most of the web users surf web sites in particular patterns. If the analysis of these usage patterns is done properly then it will be useful for recommendation system to determine which web pages are most likely to be accessed by the user in the future. All users' web access activities of a web site are stored as web log file into the web server. In the proposed system consists of sequential access pattern mining with modified CS-mine algorithm. The mined patterns are used for matching and generating web links for online recommendations.

1. Baoyao Zhou ,Siu Cheung Huia and Kuiyu Chang" An Intelligent Recommender System using Sequential Web Access Patterns" Proceedings of the 2004 lEEE Conference on Cybernetics and Intelligent Systems Singapore, 1-3 December, 2004.
2. B. Y. Zhou, S. C. Hui, and A. C. M. Fong. "CS-mine: an efficient WAP tree Mining for Web Access Patterns mining for web access patterns", the 6th Asia Pacific Web Conference (APWEBW), Hangzhou, China, April 14/17/2004, p523-532.
3. "Data Mining Concepts and Techniques" by Jiawei Han and Micheline Kamber ,second edition ,Morgan Kaufmann publisher.
4. Nasser Ahmed Sajid,Salman Zafar "Sequential Pattern Finding :A Survey" 978-1-4244-8003 , 2010 IEEE
5. Jian Pei,Jiawei Han, "Mining Access Patterns Efficiently from Web Logs" Code"–August 21,2005,Chicago, Illinois, USA. ACM.
6. C. I. Ezeife "PLWAP Sequential Mining: Open SourceCode"–August 21,2005,Chicago, Illinois, USA. ACM.
7. Xiaogang Wang,Yan Bai and Yue Li "A GSP-based Efficient Algorithm for Mining Frequent Sequences" Asia-Pacific Conference on Wearable Computing Systems 978-0-7695-4003-0/10 IEEE 2010.
8. Mohammed Zaki "SPADE An Efficient Algorithm For Mining Frequent Sequences", Machine Learning, Volume 42, Issue: 1, Publisher: Springer, Pages: 31-60,2001.
9. Ayres,J. ,Flannick, J. ,Gehrke, J. , And Yiu. "Sequential Pattern Mining Using A Bitmap Representation", In Proceedings of the 8th Acm International Conference On Knowledge Discovery And Data Mining Transaction Data Analysis 2002.
10. Jiawei Han, Jian Pei and Qiming Chen "FreeSpan: Frequent Pattern-Projected Sequential Access pattern Mining" In proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 355-359, 2000.
11. C. I. Eeife "Mining Web Log Sequential Patterns with Position Coded Pre-Order Linked WAP-Tree" Data Mining and Knowledge Discovery, Business Media, Springer Science 10, pp5-38, 2005.
12. R. Agrawal and A. swami "Mining association rules between sets of items in large databases". In Proceedings of the ACM SIGMOD international Conference on Management of Data (ACM SIGMOD'93),Washington,USA,May 1993

Web Access Pattern Algorithm Mining