A maximum entropy web recommendation system: combining collaborative and content features
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Efficient sequential access pattern mining for web recommendations
International Journal of Knowledge-based and Intelligent Engineering Systems
Using the moving average rule in a dynamic web recommendation system: Research Articles
International Journal of Intelligent Systems
Incremental and interactive mining of web traversal patterns
Information Sciences: an International Journal
A General Model for Sequential Pattern Mining with a Progressive Database
IEEE Transactions on Knowledge and Data Engineering
Modelling User Behaviour for Web Recommendation Using LDA Model
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
An effective system for mining web log
APWeb'06 Proceedings of the 8th Asia-Pacific Web conference on Frontiers of WWW Research and Development
Automatic optimization of web recommendations using feedback and ontology graphs
ICWE'05 Proceedings of the 5th international conference on Web Engineering
Personalized links recommendation based on data mining in adaptive educational hypermedia systems
EC-TEL'07 Proceedings of the Second European conference on Technology Enhanced Learning: creating new learning experiences on a global scale
Generation of web recommendations using implicit user feedback and normalised mutual information
International Journal of Knowledge and Web Intelligence
Hi-index | 0.00 |
Web recommendation systems are used to assist the user to access the most appropriate web pages that can satisfy their needs. This paper provides the web recommendation system which is based on incremental database. The incremental database contains the new navigational sequences from the user and this incremental database can be added with the existing sequence database. We have proposed a novel algorithm, called modified IncSpan, for the effectual mining of the sequential patterns from the incremental database. Finally, the performance of the proposed recommendation system is evaluated with precision, applicability and hit ratio.