Using path profiles to predict HTTP requests
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Towards adaptive Web sites: conceptual framework and case study
Artificial Intelligence - Special issue on Intelligent internet systems
A New Markov Model For Web Access Prediction
Computing in Science and Engineering
SIAM Journal on Discrete Mathematics
Evaluating the markov assumption for web usage mining
WIDM '03 Proceedings of the 5th ACM international workshop on Web information and data management
A Framework for the Evaluation of Session Reconstruction Heuristics in Web-Usage Analysis
INFORMS Journal on Computing
Selective Markov models for predicting Web page accesses
ACM Transactions on Internet Technology (TOIT)
The Practical Handbook of Internet Computing
The Practical Handbook of Internet Computing
Algorithms for variable length Markov chain modeling
Bioinformatics
Web path recommendations based on page ranking and Markov models
Proceedings of the 7th annual ACM international workshop on Web information and data management
Testing the Predictive Power of Variable History Web Usage
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Web intelligence and change discovery
Generating dynamic higher-order markov models in web usage mining
PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
Shared memories: a trail-based coordination server for robot teams
Proceedings of the 1st international conference on Robot communication and coordination
The query-flow graph: model and applications
Proceedings of the 17th ACM conference on Information and knowledge management
Query suggestions using query-flow graphs
Proceedings of the 2009 workshop on Web Search Click Data
An efficient approach for building customer profiles from business data
Expert Systems with Applications: An International Journal
Automatic keyword prediction using Google similarity distance
Expert Systems with Applications: An International Journal
Query similarity by projecting the query-flow graph
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Word AdHoc Network: Using Google Core Distance to extract the most relevant information
Knowledge-Based Systems
Using Google latent semantic distance to extract the most relevant information
Expert Systems with Applications: An International Journal
Detecting fraudulent use of cloud resources
Proceedings of the 3rd ACM workshop on Cloud computing security workshop
Are web users really Markovian?
Proceedings of the 21st international conference on World Wide Web
Modeling web usage profiles of cloud services for utility cost analysis
Proceedings of the Winter Simulation Conference
Discovering temporal hidden contexts in web sessions for user trail prediction
Proceedings of the 22nd international conference on World Wide Web companion
Collective suffix tree-based models for location prediction
Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication
Session modeling to predict online buyer behavior
Proceedings of the 2013 workshop on Data-driven user behavioral modelling and mining from social media
Proceedings of the Fourth International Conference on Learning Analytics And Knowledge
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Markov models have been widely used to represent and analyze user Web navigation data. In previous work, we have proposed a method to dynamically extend the order of a Markov chain model and a complimentary method for assessing the predictive power of such a variable-length Markov chain. Herein, we review these two methods and propose a novel method for measuring the ability of a variable-length Markov model to summarize user Web navigation sessions up to a given length. Although the summarization ability of a model is important to enable the identification of user navigation patterns, the ability to make predictions is important in order to foresee the next link choice of a user after following a given trail so as, for example, to personalize a Web site. We present an extensive experimental evaluation providing strong evidence that prediction accuracy increases linearly with summarization ability.