C4.5: programs for machine learning
C4.5: programs for machine learning
Fast discovery of association rules
Advances in knowledge discovery and data mining
Using path profiles to predict HTTP requests
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Growing decision trees on support-less association rules
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
A prediction system for multimedia pre-fetching in Internet
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
PrefixSpan: Mining Sequential Patterns by Prefix-Projected Growth
Proceedings of the 17th International Conference on Data Engineering
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Web usage mining: discovery and applications of usage patterns from Web data
ACM SIGKDD Explorations Newsletter
WhatNext: A Prediction System for Web Requests using N-gram Sequence Models
WISE '00 Proceedings of the First International Conference on Web Information Systems Engineering (WISE'00)-Volume 1 - Volume 1
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
Mining and prediction of temporal navigation patterns for personalized services in e-commerce
Proceedings of the 2006 ACM symposium on Applied computing
A framework of combining Markov model with association rules for predicting web page accesses
AusDM '06 Proceedings of the fifth Australasian conference on Data mining and analystics - Volume 61
Energy efficient strategies for object tracking in sensor networks: A data mining approach
Journal of Systems and Software
Integrating recommendation models for improved web page prediction accuracy
ACSC '08 Proceedings of the thirty-first Australasian conference on Computer science - Volume 74
Efficient mining and prediction of user behavior patterns in mobile web systems
Information and Software Technology
An integrated model for next page access prediction
International Journal of Knowledge and Web Intelligence
Mining event logs to support workflow resource allocation
Knowledge-Based Systems
A framework of online proxy-based web prefetching
WISM'12 Proceedings of the 2012 international conference on Web Information Systems and Mining
Goal attainment on long tail web sites: An information foraging approach
Decision Support Systems
A prediction framework based on contextual data to support Mobile Personalized Marketing
Decision Support Systems
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Web servers keep track of web users' browsing behavior in web logs. From these logs, one can build statistical models that predict the users' next requests based on their current behavior. These data are complex due to their large size and sequential nature. In the past, researchers have proposed different methods for building association-rule based prediction models using the web logs, but there has been no systematic study on the relative merits of these methods. In this paper, we provide a comparative study on different kinds of sequential association rules for web document prediction. We show that the existing approaches can be cast under two important dimensions, namely the type of antecedents of rules and the criterion for selecting prediction rules. From this comparison we propose a best overall method and empirically test the proposed model on real web logs.