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Book-recommendation systems are increasingly common, from Amazon to public library interfaces. However, for archives and special collections, such automated assistance has been rare. This is partly due to the complexity of descriptions (finding aids describing whole collections) and partly due to the complexity of the collections themselves (what is this collection about and how is it related to another collection?).  The American Philosophical Society Library is using circulation data collected through the collection-management software package, Aeon, to automate recommendations. In our system, which we’re calling PAL (People Also Liked), recommendations are offered in two ways: based on interests (“You’re interested in X, other people interested in X looked at these collections”) and on specific requests (“You’ve looked at Y, other people who looked at Y also looked that these collections”).  This article will discuss the development of PAL and plans for the system. We will also discuss ongoing concerns and issues, how patron privacy is protected, and the possibility of generalizing beyond any specific software solution.

PAL: Toward a Recommendation System for Manuscripts