  This thesis investigates in the use of access log data as a source of
information for identifying related scientific papers. This is done for
arXiv.org, the authority for publication of e-prints in several fields of
physics.
  Compared to citation information, access logs have the advantage of being
immediately available, without manual or automatic extraction of the citation
graph. Because of that, a main focus is on the question, how far user behavior
can serve as a replacement for explicit meta-data, which potentially might be
expensive or completely unavailable. Therefore, we compare access, content, and
citation-based measures of relatedness on different recommendation tasks. As a
final result, an online recommendation system has been built that can help
scientists to find further relevant literature, without having to search for
them actively.
