Wikipedia authors cite external references to support claims made in their articles in order to increase their validity. A large number of claims, however, do not have supporting citations, putting them in question. In this paper, we describe a study in which we attempt to retrieve relevant citations for claims using a variety of information retrieval algorithms. These algorithms are inspired by bibliometric and altmetric insights that exploit readership data from Mendeley's community and rerank results using a Bradfordising approach. The results of the small scale study indicate that both of these approaches can improve upon basic keyword-based search, typically used in digital libraries, in order to return relevant documents for unsupported claims.
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