Adventures in stochastic processes
Adventures in stochastic processes
Revisitation patterns in World Wide Web navigation
Proceedings of the ACM SIGCHI Conference on Human factors in computing systems
Foundations of statistical natural language processing
Foundations of statistical natural language processing
Discovery and Evaluation of Aggregate Usage Profiles for Web Personalization
Data Mining and Knowledge Discovery
When Is ''Nearest Neighbor'' Meaningful?
ICDT '99 Proceedings of the 7th International Conference on Database Theory
Selective Markov models for predicting Web page accesses
ACM Transactions on Internet Technology (TOIT)
Symbolic Integration I: Transcendental Functions (Algorithms and Computation in Mathematics)
Symbolic Integration I: Transcendental Functions (Algorithms and Computation in Mathematics)
A Knowledge Base for the maintenance of knowledge extracted from web data
Knowledge-Based Systems
A Web Usage Mining Framework for Mining Evolving User Profiles in Dynamic Web Sites
IEEE Transactions on Knowledge and Data Engineering
Modeling information navigation: implications for information architecture
Human-Computer Interaction
Adaptive Web Sites: A Knowledge Extraction from Web Data Approach - Volume 170 Frontiers in Artificial Intelligence and Applications
SNIF-ACT: a model of information foraging on the world wide web
UM'03 Proceedings of the 9th international conference on User modeling
Stochastic Simulation of Web Users
WI-IAT '10 Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Clustering-Based Learning Approach for Ant Colony Optimization Model to Simulate Web User Behavior
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Testing online navigation recommendations in a web site
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
Predicting web user behavior using learning-based ant colony optimization
Engineering Applications of Artificial Intelligence
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The problem of predicting human behavior has been a great challenge for several disciplines including computer science. In particular, web user browsing behavior has been studied from the machine learning point of view, a field that has been coined web usage mining (WUM). However, current WUM techniques can be negatively impacted by changes in web site structure and content (e.g. Web 2.0). The key reason behind this issue may be that machine learning algorithms learn the observed behavior according to a particular training set, but do not model the user behavior under different conditions. We propose a simulation model that mimics human interaction with the web by recovering observed navigational steps. This web usage model is inspired by a neurophysiology's stochastic description of decision making and by the information utility of web page content. The proposed model corresponds to a high-dimensional stochastic process based on the leaky competing accumulator (LCA) neural model. We solve high-dimensional issues by considering a mesh-less symbolic interpolation. As a proof-of-concept we test the web user simulation system on an academic web site by recovering most of the observed behavior (73%). Therefore, our approach operationally describes web users that seem to react as observed users confronted by changes in the web site interface.