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