Authors:
Anca-Paula Luca
and
Sabin C. Buraga
Affiliation:
“A.I. Cuza” University of Iasi, Romania
Keyword(s):
Recommender system, prediction, microformats, semantic markup, web interaction.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Enterprise Information Systems
;
Human Factors
;
Human-Computer Interaction
;
Intelligent User Interfaces
;
Machine Perception: Vision, Speech, Other
;
Physiological Computing Systems
;
User Needs
Abstract:
The multiple ways in which we rely on the information available on the web to solve increasingly more tasks encountered in day-to-day life has led to the question whether machines can help us parse the amounts of data and bring the interesting closer to us. This kind of activity, most often, requires machines to understand human defined semantics which, fortunately, can be easily done in today’s web through semantic markup. The purpose of the proposed project is to build a flexible tool that understands the behaviour of a user on the web and filters out the irrelevant data, presenting to the user only the information he/she is most interested in, while being as discreet as possible: the user is required no preference settings, no explicit feedback.