  With the increasing availability of online scholarly databases, publication
records can be easily extracted and analysed. Researchers can promptly keep
abreast of others' scientific production and, in principle, can select new
collaborators and build new research teams. A critical factor one should
consider when contemplating new potential collaborations is the possibility of
unambiguously defining the expertise of other researchers. While some
organisations have established database systems to enable their members to
manually produce a profile, maintaining such systems is time-consuming and
costly. Therefore, there has been a growing interest in retrieving expertise
through automated approaches. Indeed, the identification of researchers'
expertise is of great value in many applications, such as identifying qualified
experts to supervise new researchers, assigning manuscripts to reviewers, and
forming a qualified team. Here, we propose a network-based approach to the
construction of authors' expertise profiles. Using the MEDLINE corpus as an
example, we show that our method can be applied to a number of widely used data
sets and outperforms other methods traditionally used for expertise
identification.
