bX Recommender trial: scholarly article recommendations

From April through mid-June 2011, the University of California Libraries are experimenting with a 2-month trial of bX Recommender, a service that points users to relevant scholarly articles on the topics they’re researching.

How does it work?
bX Recommender is a tool embedded in UC-eLinks that leads you to other articles like the one you’ve found. It is similar to other recommender tools such as Amazon’s “Customers who bought this item also bought…” or Netflix’s preferences feature.

Are all articles covered?
Recommendations will only appear for articles with full text available online.  bX generates its recommendations based on actual use by researchers in academic libraries who use link resolver services (like UC-eLinks) all over the world. The service makes connections between articles as searchers discover and access them, so it is continually being refined and improved as more people use it and contribute their data to the system.

How do I use it?
Click on the UC-eLinks button when you find an article in an article database, or when you look up a specific citation using UC-eLinks Citation Linker (must use full exact article title), and scan down to find the recommended articles. It should look like this:


Things to note
Your feedback on this trial is important!  Please use the “Feedback on bX BETA” link in the UC-eLinks window to make comments or report problems.

The UC-eLinks service is available to anyone using computers on the UC Berkeley campus network.    Off-campus use of UC-eLinks is open only to UC Berkeley students, faculty and staff members, using our proxy server or VPN system.