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228 Selected Studies on Software and Information Systems
consists of 17 text fields, 20 choice boxes, 6 check boxes, and requires vertical scrolling before
a query can be submitted [31]. Despite the interface complexity, users search preferences
are limited in several ways (e.g., only two genres can be combined together). Moreover,
form-based graphical interface have difficulties capturing all possibilities including negation,
quantification etc. Some believe [31] that a solution could be a natural language processing
engine which is communicating with the user in a dialogue form similar to human-to-human
communication allowing the user to express any kind of preferences.
Last but not least, it is important to mention that the form-based methods force the users
to spend too much time with activities which are not part of the user’s goals and are not the
reason why the user came to use the system (e.g., filling the forms instead of learning). User
might easily get discouraged to use the system, or might lose the concentration etc.
In [23] authors use the explicit user modeling approach in an interesting way. The
user model is built with the active user’s participation (“interactive user modeling” also
called “user model elicitation”) in the educational domain. They create a system called
OntoAIMS which uses OWL-OLM (OWL based framework for open user modeling) to
elicit user (learner) model. It uses a dialogue-based approach where user composes composes
statements by constructing diagrams using basic graphical operations such as “create”,
“delete” or “edit” a concept or a relation between concepts and defining his intention, e.g.
to “answer”, “question”, “agree”, “disagree”, “suggest topic”. OWL-OLM processes these
answers to build user’s conceptual model based on the domain concepts. When the required
aspects of the user’s conceptualization have been covered, the dialog can be terminated.
Implicit User Modeling
While explicit acquisition of information can be with no doubt used to alleviate cold-start
problem (as user fills-in the form before the actual usage of the system), this is not necessarily
the case in implicit acquisition information and thus implicit user modeling. It depends on
the speed, how fast the user model converges to something useful, reflecting reality (i.e., how
many actions (clicks) and/or sessions are necessary for the system to estimate a correct user
model).
Implicit user modeling can be divided into three categories, depending on the complexity
of the process:
– Monitoring Access to Resources;
– Monitoring User Feedback;
– Monitoring User Behavior.
Monitoring Access to Resources Users visit the web-based system in order to achieve a
goal and what they actually do to achieve it is the formulation (visual or textual) of queries for
system’s resources and subsequent processing (i.e., reading) of those resources. Web-based
system can hold evidence of individual accesses to the resources and provide adaptation
upon this evidence.
This approach is used successfully in educational adaptive systems. For example, AHA!
system [21] creates two records for each user’s access to a page (resource): one record for the