User interface directions for the Web
Communications of the ACM
Automatic personalization based on Web usage mining
Communications of the ACM
A vector space model for automatic indexing
Communications of the ACM
Web mining for web personalization
ACM Transactions on Internet Technology (TOIT)
Integrating Web Usage and Content Mining for More Effective Personalization
EC-WEB '00 Proceedings of the First International Conference on Electronic Commerce and Web Technologies
Web Personalization Techniques for E-commerce
AMT '01 Proceedings of the 6th International Computer Science Conference on Active Media Technology
Web Usage Mining as a Tool for Personalization: A Survey
User Modeling and User-Adapted Interaction
Personalised hypermedia presentation techniques for improving online customer relationships
The Knowledge Engineering Review
Acquisition and Maintenance of Knowledge for Online Navigation Suggestions
IEICE - Transactions on Information and Systems
Adaptive Web SitesA Knowledge Extraction from Web Data Approach
Proceedings of the 2008 conference on Adaptive Web Sites: A Knowledge Extraction from Web Data Approach
Innovations in intelligent agents and web
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
A neurology-inspired model of web usage
Neurocomputing
| Hi-index | 0.00 |
An online navigation recommendation system provides the prospective web site visitor with a set of pages that could be of his/her interest. Because the recommendations are given during the user session in the web site, it could be very damaging for the overall business of the company owning the web site, if the recommendations are erroneous. In this paper, we introduce an a priori method to estimate the success of an online navigation recommendation. The methodology was tested in a recommendation system that works with the data generated in a real web site, which proved the effectiveness of our approach.