From user access patterns to dynamic hypertext linking
Proceedings of the fifth international World Wide Web conference on Computer networks and ISDN systems
Design considerations for the Apache server API
Proceedings of the fifth international World Wide Web conference on Computer networks and ISDN systems
SpeedTracer: a Web usage mining and analysis tool
IBM Systems Journal
Personalization on the Net using Web mining: introduction
Communications of the ACM
Automatic personalization based on Web usage mining
Communications of the ACM
ACM SIGKDD Explorations Newsletter
Web mining for web personalization
ACM Transactions on Internet Technology (TOIT)
Adaptive Web Sites: Conceptual Cluster Mining
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
SUGGEST: A Web Usage Mining System
ITCC '02 Proceedings of the International Conference on Information Technology: Coding and Computing
Item-based top-N recommendation algorithms
ACM Transactions on Information Systems (TOIS)
On-line Generation of Suggestions for Web Users
ITCC '04 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'04) Volume 2 - Volume 2
Web path recommendations based on page ranking and Markov models
Proceedings of the 7th annual ACM international workshop on Web information and data management
Usage-Based PageRank for Web Personalization
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
A privacy preserving web recommender system
Proceedings of the 2006 ACM symposium on Applied computing
Dynamic personalization of web sites without user intervention
Communications of the ACM - Spam and the ongoing battle for the inbox
An intelligent system integrated with fuzzy ontology for product recommendation and retrieval
FS'07 Proceedings of the 8th Conference on 8th WSEAS International Conference on Fuzzy Systems - Volume 8
Solution Architecture for Visitor Segmentation and Recommendation Generation in Real Time
EC-Web '08 Proceedings of the 9th international conference on E-Commerce and Web Technologies
Collaborative filtering adapted to recommender systems of e-learning
Knowledge-Based Systems
WebPUM: A Web-based recommendation system to predict user future movements
Expert Systems with Applications: An International Journal
A new collaborative filtering metric that improves the behavior of recommender systems
Knowledge-Based Systems
The effect of sparsity on collaborative filtering metrics
ADC '09 Proceedings of the Twentieth Australasian Conference on Australasian Database - Volume 92
e-learning experience using recommender systems
Proceedings of the 42nd ACM technical symposium on Computer science education
ARS: web page recommendation system for anonymous users based on web usage mining
ECS'10/ECCTD'10/ECCOM'10/ECCS'10 Proceedings of the European conference of systems, and European conference of circuits technology and devices, and European conference of communications, and European conference on Computer science
WebKDD'05 Proceedings of the 7th international conference on Knowledge Discovery on the Web: advances in Web Mining and Web Usage Analysis
Introducing semantics in web personalization: the role of ontologies
EWMF'05/KDO'05 Proceedings of the 2005 joint international conference on Semantics, Web and Mining
A framework for collaborative filtering recommender systems
Expert Systems with Applications: An International Journal
Ontology driven bee's foraging approach based self adaptive online recommendation system
Journal of Systems and Software
RESYGEN: A Recommendation System Generator using domain-based heuristics
Expert Systems with Applications: An International Journal
A trajectory-based recommender system for tourism
AMT'12 Proceedings of the 8th international conference on Active Media Technology
Personal and Ubiquitous Computing
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In this paper we propose a WUM recommender system, called SUGGEST 3.0, that dynamically generates links to pages that have not yet been visited by a user and might be of his potential interest. Differently from the recommender systems proposed so far, SUGGEST 3.0 does not make use of any off-line component, and is able to manage Web sites made up of pages dynamically generated. To this purpose SUGGEST 3.0 incrementally builds and maintains historical information by means of an incremental graph partitioning algorithm, requiring no off-line component. The main innovation proposed here is a novel strategy that can be used to manage large Web sites. Experiments, conducted in order to evaluate SUGGEST 3.0 performance, demonstrated that our system is able to anticipate users' requests that will be made farther in the future, introducing a limited overhead on the Web server activity.