CHI '86 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
From user access patterns to dynamic hypertext linking
Proceedings of the fifth international World Wide Web conference on Computer networks and ISDN systems
Adaptive Web sites: automatically synthesizing Web pages
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Using path profiles to predict HTTP requests
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Probabilistic Languages: A Review and Some Open Questions
ACM Computing Surveys (CSUR)
Efficient Data Mining for Path Traversal Patterns
IEEE Transactions on Knowledge and Data Engineering
WUM - A Tool for WWW Ulitization Analysis
WebDB '98 Selected papers from the International Workshop on The World Wide Web and Databases
Web Mining: Information and Pattern Discovery on the World Wide Web
ICTAI '97 Proceedings of the 9th International Conference on Tools with Artificial Intelligence
Adaptive web sites: an AI challenge
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
A probabilistic approach to navigation in Hypertext
Information Sciences: an International Journal
Cut-and-Pick Transactions for Proxy Log Mining
EDBT '02 Proceedings of the 8th International Conference on Extending Database Technology: Advances in Database Technology
Mining interest navigation patterns based on hybrid Markov model
ICCOMP'06 Proceedings of the 10th WSEAS international conference on Computers
Mining interest navigation patterns based on hybrid markov model
FQAS'06 Proceedings of the 7th international conference on Flexible Query Answering Systems
| Hi-index | 0.00 |
In previous work we have proposed a data mining model to capture user web navigation patterns, which models the navigation sessions as a hypertext probabilistic grammar. The grammar's higher probability strings correspond to the user preferred trails and an algorithm was given to find all strings with probability above a threshold. Herein, we propose a heuristic aimed at finding longer trails composed of links whose average probability is above the threshold. A dynamic threshold is provided whose value is at all times proportional to the length of the trail being evaluated. We report on experiments with both real and synthetic data which were conducted to assess the heuristic's utility.