Web server workload characterization: the search for invariants
Proceedings of the 1996 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Self-similarity in World Wide Web traffic: evidence and possible causes
IEEE/ACM Transactions on Networking (TON)
Capacity Planning for Web Services: metrics, models, and methods
Capacity Planning for Web Services: metrics, models, and methods
Discovery of Web Robot Sessions Based on their Navigational Patterns
Data Mining and Knowledge Discovery
Summary of WWW characterizations
World Wide Web
A hierarchical and multiscale approach to analyze E-business workloads
Performance Evaluation
Web crawling ethics revisited: Cost, privacy, and denial of service
Journal of the American Society for Information Science and Technology
Securing web service by automatic robot detection
ATEC '06 Proceedings of the annual conference on USENIX '06 Annual Technical Conference
Discovering New Trends in Web Robot Traffic Through Functional Classification
NCA '08 Proceedings of the 2008 Seventh IEEE International Symposium on Network Computing and Applications
Web robot detection: A probabilistic reasoning approach
Computer Networks: The International Journal of Computer and Telecommunications Networking
Proceedings of the 2009 workshop on Web Search Click Data
Workload Characterization of a Large Systems Conference Web Server
CNSR '09 Proceedings of the 2009 Seventh Annual Communication Networks and Services Research Conference
An investigation of web crawler behavior: characterization and metrics
Computer Communications
Foundations and Trends in Information Retrieval
A comparison of web robot and human requests
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
An extensive study of Web robots traffic
Proceedings of International Conference on Information Integration and Web-based Applications & Services
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Web logs are an important source of information to describe and understand the traffic of the servers and its characteristics. The analysis of these logs is rather challenging because of the large volume of data and the complex relationships hidden in these data. Our investigation focuses on the analysis of the logs of two Web servers and identifies the main characteristics of their workload and the navigation profiles of crawlers and human users visiting the sites. The classification of these visitors has shown some interesting similarities and differences in term of traffic intensity and its temporal distribution. In general, crawlers tend to re-visit the sites rather often, even though they seldom send bursts of requests to reduce their impact on the servers resources. The other clients are also characterized by periodic patterns that can be effectively represented by few principal components.