Recommender Systems in the Social Web: Heterogeneity and Time Dimension
Recommender Systems in the Social Web: Heterogeneity and Time Dimension (ReSHeT) is a project at the Autonomous University of Madrid.
From the project website:
The Social Web has originated an unprecedented growth in the use of social networks, folksonomies, blogs, wikis and similar systems. These tools encourage collaboration and exchange of information among users, creating a huge and growing amount of digital resources that often overwhelms the human processing capabilities. To address this problem, recommender systems filter the available information, and suggest the user those resources he may be interested in, without the need of explicitly looking for them.
The partners of the project include:
- The Information Retrieval Group at UAM.