In
environments such as the Web in which people have access to a large
amount of heterogeneous information sources, it is important to provide
advanced solutions to the problems of acquisition, mediation and
maintenance of information relevant to a user. In environments with
these characteristics, users usually perform repetitive tasks such as
browsing, filtering and searching for relevant information. This
scenario opens interesting research challenges for the development of
mechanisms to analyze the behavior of users on the web in order to find
patterns that enable the prediction of the users' intentions. At a first
sight, surfing the Web can be a simple and intuitive task. However,
users often experience difficulties in finding the information or
services needed using conventional search engines and directories, or
when they whant to return to previously visited sites. A common problem
with traditional Web search engines is that many users have difficulties
to express the queries or keywords that will lead them to get the
information they are seeking for. On the other hand, in a query,
potentially relevant results are immersed in a large number of results
that have little to do with the actual search intention of the users.
This project proposes the study of mechanisms to detect the user's
intent in order to provide proactive support to help users to achieve
their goals. Director: Dr. Marcelo G. Armentano Collaborators: Dr. Analía Amandi, Dr. Silvia Schiaffino, Dr. Daniela Godoy |
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