Algorithms for clustering data
Algorithms for clustering data
Bayesian Clustering for Unsupervised Estimation of Surface and Texture Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
The World-Wide Web: quagmire or gold mine?
Communications of the ACM
Patterns of search: analyzing and modeling Web query refinement
UM '99 Proceedings of the seventh international conference on User modeling
ACM Computing Surveys (CSUR)
Adaptive interfaces for ubiquitous web access
Communications of the ACM - The Adaptive Web
Using Markov models for web site link prediction
Proceedings of the thirteenth ACM conference on Hypertext and hypermedia
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Plight of the Navigator: Solving the Navigation Problem for Wireless Portals
AH '02 Proceedings of the Second International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems
PTV: Intelligent Personalised TV Guides
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of 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
Rhythm modeling, visualizations and applications
Proceedings of the 16th annual ACM symposium on User interface software and technology
Hourly analysis of a very large topically categorized web query log
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Predicting navigation patterns on the mobile-internet using time of the week
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
Mobile web surfing is the same as web surfing
Communications of the ACM - Self managed systems
Letizia: an agent that assists web browsing
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Adaptive web navigation for wireless devices
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Coordinate: probabilistic forecasting of presence and availability
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Temporal rules for predicting user navigation in the mobile web
AH'06 Proceedings of the 4th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems
Data preparation of web log files for marketing aspects analyses
ICDM'06 Proceedings of the 6th Industrial Conference on Data Mining conference on Advances in Data Mining: applications in Medicine, Web Mining, Marketing, Image and Signal Mining
| Hi-index | 0.00 |
Many systems attempt to forecast user navigation in the Internet through the use of past behavior, preferences and environmental factors. Most of these models overlook the possibility that users may have many diverse sets of preferences. For example, the same person may search for information in different ways at night (when they are pursuing their hobbies and interests) as opposed to during the day (when they are at work). Thus, most users may well have different sets of preferences at different times of the day and behave differently in accordance with those preferences. In this paper, we present clustering methods for creating time dependent models to predict user navigation patterns; these methods allow us to segment log files into appropriate groups of navigation behaviour. The benefits of these methods over more established methods are highlighted. An empirical analysis is carried out on a sample of usage logs for Wireless Application Protocol (WAP) browsing as empirical support for the technique.