Data mining and the Web: past, present and future
Proceedings of the 2nd international workshop on Web information and data management
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
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
Effective personalization based on association rule discovery from web usage data
Proceedings of the 3rd international workshop on Web information and data management
A New Markov Model For Web Access Prediction
Computing in Science and Engineering
Evaluating the markov assumption for web usage mining
WIDM '03 Proceedings of the 5th ACM international workshop on Web information and data management
A Web page prediction model based on click-stream tree representation of user behavior
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Building Association-Rule Based Sequential Classifiers for Web-Document Prediction
Data Mining and Knowledge Discovery
Selective Markov models for predicting Web page accesses
ACM Transactions on Internet Technology (TOIT)
A clickstream-based collaborative filtering personalization model: towards a better performance
Proceedings of the 6th annual ACM international workshop on Web information and data management
WAM-Miner: in the search of web access motifs from historical web log data
Proceedings of the 14th ACM international conference on Information and knowledge management
Mining Sequential Association-Rule for Improving WEB Document Prediction
ICCIMA '05 Proceedings of the Sixth International Conference on Computational Intelligence and Multimedia Applications
Mining Sequential Association-Rule for Improving WEB Document Prediction
ICCIMA '05 Proceedings of the Sixth International Conference on Computational Intelligence and Multimedia Applications
Mining longest repeating subsequences to predict world wide web surfing
USITS'99 Proceedings of the 2nd conference on USENIX Symposium on Internet Technologies and Systems - Volume 2
Augmenting Gesture Animation with Motion Capture Data to Provide Full-Body Engagement
IVA '09 Proceedings of the 9th International Conference on Intelligent Virtual Agents
Using domain ontology for semantic web usage mining and next page prediction
Proceedings of the 18th ACM conference on Information and knowledge management
A User Behavior Perception Model Based on Markov Process
WISM '09 Proceedings of the International Conference on Web Information Systems and Mining
An integrated model for next page access prediction
International Journal of Knowledge and Web Intelligence
Combining markov models and association analysis for disease prediction
ITBAM'11 Proceedings of the Second international conference on Information technology in bio- and medical informatics
| Hi-index | 0.00 |
The importance of predicting Web users' behaviour and their next movement has been recognised and discussed by many researchers lately. Association rules and Markov models are the most commonly used approaches for this type of prediction. Association rules tend to generate many rules, which result in contradictory predictions for a user session. Low order Markov models do not use enough user browsing history and therefore, lack accuracy, whereas, high order Markov models incur high state space complexity. This paper proposes a novel approach that integrates both association rules and low order Markov models in order to achieve higher accuracy with low state space complexity. A low order Markov model provides high coverage with low state space complexity, and association rules help achieve better accuracy.