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User Modeling for Personalized Web-Based Systems 231
The acquired data are not necessarily used to compute a feedback value as it is in the
implicit feedback approach. The system could use the data to estimate other types of user
characteristics.
The nature of acquired data implies that this approach is especially useful for open and
ever-changing information spaces and non-linear navigational model. Many e-Learning
courses are “forcing” the user to follow a predefined “optimal” route through the content
(usually a linear sequence of pages without any branching). This could lead to uninteresting
data of no use for further analysis as user’s characteristics and background could not
influence user’s browsing behavior (as the user follows the route predefined by a course
author) [40].
The approach is appropriate considering user involvement into the user modeling process.
User is actively using the system (e.g., is taking an electronic course), which is exactly
the reason why the user visited the system. Whole data collection and processing tasks are
performed in the background, without user’s intervention.
Majority of systems collect user behavior data on a server side in a form of log file. This
results in lack of records for actions which do not reach the server. A typical example is
usage of back button in the web browser which does not re-request the page from the server
but use the cached copy instead. Server is thus not aware of the exact time user spent by
viewing the page. Another example is user interaction with active page elements (e.g., using
javascript) which are not communicating with a server.
The data collection part of user modeling (user action monitoring) is independent of the
actual modeling process. In fact, it is identical to e.g., data collection for purpose of web
sites usability evaluation. In [53] authors note that usability evaluation performed only on
the server side is ineffective as it is too coarse grained, not providing enough details. They
note that to acquire comprehensive data about web application usage, one need to employ
client side monitoring. This was recognized also in the community of adaptive web-based
systems [42, 18, 28, 38].
However, client side data availability can not be guaranteed because we have no control
on logger execution, as it is on a server side. Therefore, the most suitable approach is to use
the combination of the two logging approaches: use a server side logging and complete it
with data from client side logging [4].
Software Solutions for Data Collection. Several software tools were developed for the
purpose of web sites usability evaluation. Some representatives of such tools are WebVIP 6 ,
WET [26], UAR [59] or Click [5]. WebVip (Web Variable Instrumenter Program) is a tool to
augment traditional user testing on a given set of tasks. It allows for setting of actions to
be logged, generates Javascript scripts and embeds them into the target pages. The scripts
(executed on a client side within user’s browser) creates a FLUD (Framework for Logging
Usability Data) records. WebVip needs to thoroughly modify every HTML page of a web
site and thus needs a static snapshot of a website apriori to its execution, which is obviously
a severe disadvantage.
WET (Web Event-logging Tool) is also based on JavaScript technology. When using it, is is
sufficient to add a reference to a script file into a header part of every HTML page, so we do not
6 WebVip, http://zing.ncsl.nist.gov/WebTools/WebVIP/overview.html