From your previous experience with PUMA you may know that a typical way of browsing is to select one or more tags to retrieve a list of resources (e.g. bookmarks) ordered by date. This helps to discover the most recent posts; but it does not present the most relevant information considering the specific tag.
For finding highly relevant resources for a given tag, our research group has developed an algorithm called FolkRank. Its idea is similar to Google's PageRank algorithm, i.e. it analyzes the link structure between users, tags and resources iteratively in order to calculate relevance.
FolkRank can be accessed by adding ?order=folkrank to the URL or by clicking "order by FolkRank" under the search bar on a tag page. For instance, when you analyze the results for the tag "www", you can see that highly relevant bookmarks (in a research community) like the WWW conference websites are found at the very top of the retrieved list.
Furthermore, FolkRank is able to calculate highly "relevant" users for a given tag:
The relevant users may be experts in a certain research area and a good starting point in networking with colleagues interested in similar topics as you are.
Click here to go back to beginner's area and learn more about the basic functions.
