Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
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)
Spatial join selectivity using power laws
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
A methodology for workload characterization of E-commerce sites
Proceedings of the 1st ACM conference on Electronic commerce
Using the fractal dimension to cluster datasets
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
In search of invariants for e-business workloads
Proceedings of the 2nd ACM conference on Electronic commerce
Characterizing the scalability of a large web-based shopping system
ACM Transactions on Internet Technology (TOIT)
Characterizing reference locality in the WWW
DIS '96 Proceedings of the fourth international conference on on Parallel and distributed information systems
Scaling for E Business: Technologies, Models, Performance, and Capacity Planning
Scaling for E Business: Technologies, Models, Performance, and Capacity Planning
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
Estimating the Selectivity of Spatial Queries Using the `Correlation' Fractal Dimension
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
A hierarchical and multiscale approach to analyze E-business workloads
Performance Evaluation
Cluster Analysis
IEEE Internet Computing
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Understanding the workload of Web and e-business sites is a fundamental step in sizing the IT infrastucture that supports these sites and in planning for their evolution so that Quality of Service (QoS) golas are met within cost constraints. This paper presents two approaches for characterzing e-business sessions: distace-based and fractal (session similarity). We apply both approaches to an actual e-business workload to understand what customers do, what navigational patterns they follow, and to identify groups of users that have similar behaviour. We also present the benefits and drawbacks of both approaches. The main contribution of this work is presentation of techniques that improve the process of workload characterization.