Log is a concept commonly used in computer science; in fact, log data are collected by an operating system to make a permanent record of events during the usage of the operating system itself. This is done to better support its operations, and in particular its recovery procedures. Due to the experience gained in the management of operating systems and many application systems that manage permanent data, log procedures are commonly put in place also to collect and store data on the usage of an application system by its users. Initially, these data were mainly used to manage recovery procedures of the application system, but over time it became apparent that they could also be used to study the usage of the application by its users, and to better adapt the system to the objectives the users were expecting to reach. In the context of the Web, the storage and the analysis of Web log files are mainly used to gain knowledge on the users and improve the services offered by a Web portal, without the need to bother the users with explicit collection of information on use of the portal.

In general, users studies and logs are used in a separate way, since they are adopted with different aims in mind. Ingwersen and Jarvelin reported that it seems more scientifically informative to combine logs together with 
observation in naturalistic settings. Pharo and Jarvelin suggested a systematic use of triangulation of different data collection techniques as a general approach in order to get better knowledge of the Web information search process. Taking inspiration from this general approach, we have conceived a method of combining implicit and explicit user interaction data to gain information to be used for personalization purposes. 
So, data log analysis can be combined with the results of data derived from user studies to evaluate information access services.