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
Mining Access Patterns Efficiently from Web Logs
PADKK '00 Proceedings of the 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Current Issues and New Applications
Improving the Efficiency of Interactive Sequential Pattern Mining by Incremental Pattern Discovery
HICSS '03 Proceedings of the 36th Annual Hawaii International Conference on System Sciences (HICSS'03) - Track 3 - Volume 3
Web usage mining: discovery and applications of usage patterns from Web data
ACM SIGKDD Explorations Newsletter
Capturing User Access Patterns in the Web for Data Mining
ICTAI '99 Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence
Web Mining: Information and Pattern Discovery on the World Wide Web
ICTAI '97 Proceedings of the 9th International Conference on Tools with Artificial Intelligence
Mining Traveling and Purchasing Behaviors of Customers in Electronic Commerce Environment
EEE '04 Proceedings of the 2004 IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE'04)
| Hi-index | 0.00 |
Web mining is one of the mining technologies, which applies data mining technique in large amount of web data to improve the web services. Web traversal pattern mining discovers most of users’ access patterns from web logs. When we understand the users’ behaviors, we can make some appropriate actions for different purposes. However, it is considerably difficult to select a perfect minimum support threshold during the mining procedure to find the interesting rules. Even though the experienced experts, they also cannot determine the appropriate minimum support to find the interesting rules. Thus, we must constantly adjust the minimum support until the satisfactory mining results can be found. This will waste a lot of time on these repeating mining processes with the same data. Therefore, many researchers pay attention to the interactive data mining in recent years. The essence of interactive data mining is that we can use the previous mining results to reduce the unnecessary processes when the minimum support is changed. In this paper, we propose an efficient interactive web traversal pattern mining algorithm to reduce the mining time and make the mining results to satisfy the users’ requirements.