  Term suggestion or recommendation modules can help users to formulate their
queries by mapping their personal vocabularies onto the specialized vocabulary
of a digital library. While we examined actual user queries of the social
sciences digital library Sowiport we could see that nearly one third of the
users were explicitly looking for author names rather than terms. Common term
recommenders neglect this fact. By picking up the idea of polyrepresentation we
could show that in a standardized IR evaluation setting we can significantly
increase the retrieval performances by adding topical-related author names to
the query. This positive effect only appears when the query is additionally
expanded with thesaurus terms. By just adding the author names to a query we
often observe a query drift which results in worse results.
