Efficient Data Mining for Path Traversal Patterns
IEEE Transactions on Knowledge and Data Engineering
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
An Efficient Data Mining Technique for Discovering Interesting Sequential Patterns
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
An incremental data mining algorithm for discovering web access patterns
International Journal of Business Intelligence and Data Mining
APD-A Tool for Identifying Behavioural Patterns Automatically from Clickstream Data
KES '07 Knowledge-Based Intelligent Information and Engineering Systems and the XVII Italian Workshop on Neural Networks on Proceedings of the 11th International Conference
Identifying web navigation behaviour and patterns automatically from clickstream data
International Journal of Web Engineering and Technology
Hi-index | 0.00 |
In this paper, we propose a data mining technology to find nonsimple frequent traversal patterns in a web environment where users can travel from one object to another through the corresponding hyperlinks. We keep track and remain the original user traversal paths in a web log, and apply the proposed data mining techniques to discover the complete traversal path which is traversed by a sufficient number of users, that is, non-simple frequent traversal patterns, from web logs. The non-simple frequent traversal patterns include forward and backward references, which are used to suggest potentially interesting traversal path to the users. The experimental results show that the discovered patterns can present the complete browsing paths traversed by most of the users and our algorithm outperforms other algorithms in discovered information and execution times.