About SCRAT Group
SCRAT Group is part of ARDiS Lab, that belongs to the Computer Science Department
of the University of Cyprus. SCRAT Group was launched in the year 2007. The main
reasearch area is Web Personalization and Adaptation, eLearning, Semantics, Meta
Information, Intelligent Systems.
Our Vision is to develop a dynamic comprehensive personalization filter that will
be based on the automatic extraction of humans' most intrinsic values, namely, User
Perceptual Preference Characteristics, and serve as the prime element of any entity
(Web-based system, advanced training system, mobile system, virtual environment,
spacecraft, aircraft, robot, etc.), liable to accept any type of semantic content,
alter and return it, adjusted to the unique characteristics and preferences of the
user. User Perceptual Preference Characteristics (UPPC) are all "the critical factors
that influence the visual, mental and emotional processes liable of manipulating
the newly information received and building upon prior knowledge, that is different
for each user or user group. These characteristics determine the visual attention,
cognitive and emotional processing taking place throughout the whole process of
accepting an object of perception (stimulus) until the comprehensive response to
it".
Main Research Objectives:
- An extensive research of the Cognitive Psychology domains related to visual, cognitive
and emotional processing.
- The development of a three-dimensional model composed of the following optimized
parameters: (a) Visual attention, cognitive processing (speed of processing, control
of processing and working memory span), (b) cognitive styles, and (c) emotion control
(core anxiety, application specific anxiety, current anxiety, and emotion regulation).
- The creation of a comprehensive user profile, that is composed of the "traditional"
user characteristics (i.e. knowledge, goals, background, experience, preferences,
activities, etc.), device / channels characteristics (i.e. device screen size, bandwidth,
input method etc.), and the UPPC (cognitive and emotional parameters).
- The development of an open and interoperable Web-based architecture, that is based
on the abovementioned characteristics (profile).
- The evaluation of the system and model's impact into the computer-mediated information
space.
- The extension of the system's scope on more generic Web structures and the evaluation
of the extended system.
- The measurement of the users' emotional state with the automatic extraction of body
signals (blood pressure, galvanic skin etc.) in relation to users' performance.
Subsequent research objectives:
-
- The identification of the effect of the rules formulated by the combination of data
extracted from sensors and the psychological state of a user, onto the actual content
(i.e. marketing, eHealth, etc.) that could be delivered to him/her;
- The definition of the Intelligent User Interface and rules that will alter the content
to be delivered based on the signals taken and the individual differences (as well
as current emotional state) of the users. This will signify the importance of adopting
the incoming content in such a way that will be most suitable for the users;
- The further identification of rules with regards to the quantity or the form data
need to be altered and delivered, so to be more efficient and effective when conveyed
to each user in terms of comprehension and information assimilation;
- The combination of the users' anxiety levels, taken with the use of biometrical
sensors metrics (blood pressure, galvanic skin etc.), with various cognitive typologies
and the potential mapping rules of these values to any content, for delivering a
personalized and adapted results to their current emotional states.
- The construction of a Semantic Web editor for automated development of personalized
content.
- The further evaluation of the impact of cognitive aspects into computer-mediated
environments with the use of an Eye-tracker device.
- The further investigation of the constraints and challenges arise from the implementation
of such issues and implement the abovementioned model into more advanced computer-mediated
entities in order to further evaluate the validity of their impact.