Usage tracking by public information system mediator

Abstract

Keeping track of the users' activity is a common scenario in the Internet nowadays. Large volumes of usage data are collected and stored on Web servers, proxies and clients throughout the network on a daily basis. Properly interpreted, these data are a valuable resource for determining the effective marketing strategies, automatic generation of personalized user profiles, and network performance optimization. Information and data correlation needed to perform these tasks are extracted from the collected data through data mining process. This work presents the usage tracking performed by the public information system mediator. The mediator provides a design-time support for the development of distributed services and a run-time support for their execution. One of the aspects of the service run-time support is collecting the service's usage. The usage collecting mechanism introduced by the mediator is adaptable through the service specific filters. Collected usage data are grouped into general and service specific usage data. Based on these two groups of usage data, two types of data mining processes are being proposed. General data mining uses general usage data to extract the usage patterns and optimize performance of the mediator. Service specific data mining is done by the service vendor through the semantic interpretation of service specific usage data and is used for extending the service offerings and service performance optimization.