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