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The World Wide Web is a great source of products and
services available to people. Scientists have made a
huge effort to create effective strategies to
personalize those products/services for anyone
willing to use them. The personalization may be
provided by Recommender Systems which are able to
match people's preferences to specific products or
services.
Scientists from different research areas such as
Psychology, Neurology and Affective Computing agree
that human reasoning and decision-making are hardly
ever affected by psychological aspects. Thus, to
maintain the same level of personalized service
provided by humans, computers should
also "reason", taking into account users'
psychological aspects.
Nevertheless, the psychological aspects have,
unfortunately, not been highly applied in
Recommender Systems during their decision-making process.
In this work we discuss the evidences that the use of
Personality Traits
in Recommender Systems might be coherent and
effective for the improvement of the recommendations
for users and, therefore, act proactively towards
users' needs, offering more adaptable products and
services according to their future needs.
services available to people. Scientists have made a
huge effort to create effective strategies to
personalize those products/services for anyone
willing to use them. The personalization may be
provided by Recommender Systems which are able to
match people's preferences to specific products or
services.
Scientists from different research areas such as
Psychology, Neurology and Affective Computing agree
that human reasoning and decision-making are hardly
ever affected by psychological aspects. Thus, to
maintain the same level of personalized service
provided by humans, computers should
also "reason", taking into account users'
psychological aspects.
Nevertheless, the psychological aspects have,
unfortunately, not been highly applied in
Recommender Systems during their decision-making process.
In this work we discuss the evidences that the use of
Personality Traits
in Recommender Systems might be coherent and
effective for the improvement of the recommendations
for users and, therefore, act proactively towards
users' needs, offering more adaptable products and
services according to their future needs.