Randomized algorithms
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Link prediction and path analysis using Markov chains
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
A general probabilistic framework for clustering individuals and objects
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Visualization of navigation patterns on a Web site using model-based clustering
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Towards adaptive Web sites: conceptual framework and case study
Artificial Intelligence - Special issue on Intelligent internet systems
Proceedings of the 11th international conference on World Wide Web
Web mining for web personalization
ACM Transactions on Internet Technology (TOIT)
User-Driven Navigation Pattern Discovery from Internet Data
WEBKDD '99 Revised Papers from the International Workshop on Web Usage Analysis and User Profiling
Data Mining of User Navigation Patterns
WEBKDD '99 Revised Papers from the International Workshop on Web Usage Analysis and User Profiling
Probabilistic User Behavior Models
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
SEWeP: using site semantics and a taxonomy to enhance the Web personalization process
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
An Online Recommender System for Large Web Sites
WI '04 Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence
FS-Miner: efficient and incremental mining of frequent sequence patterns in web logs
Proceedings of the 6th annual ACM international workshop on Web information and data management
Mining history of changes to web access patterns
PKDD '04 Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
Structure and value synopses for XML data graphs
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Web path recommendations based on page ranking and Markov models
Proceedings of the 7th annual ACM international workshop on Web information and data management
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
Web Page Prediction Based on Conditional Random Fields
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
MUADDIB: A distributed recommender system supporting device adaptivity
ACM Transactions on Information Systems (TOIS)
Web page ranking based on fuzzy and learning automata
Proceedings of the International Conference on Management of Emergent Digital EcoSystems
TripleRank: Ranking Semantic Web Data by Tensor Decomposition
ISWC '09 Proceedings of the 8th International Semantic Web Conference
A framework to compute page importance based on user behaviors
Information Retrieval
Efficient ad-hoc search for personalized PageRank
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
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Recommendation algorithms aim at proposing "next" pages to a user based on her current visit and the past users' navigational patterns. In the vast majority of related algorithms, only the usage data are used to produce recommendations, whereas the structural properties of the Web graph are ignored. We claim that taking also into account the web structure and using link analysis algorithms ameliorates the quality of recommendations. In this paper we present UPR, a novel personalization algorithm which combines usage data and link analysis techniques for ranking and recommending web pages to the end user. Using the web site's structure and its usage data we produce personalized navigational graph synopses (prNG) to be used for applying UPR and produce personalized recommendations. Experimental results show that the accuracy of the recommendations is superior to pure usage-based approaches.