  The growing impact of preprint servers enables the rapid sharing of
time-sensitive research. Likewise, it is becoming increasingly difficult to
distinguish high-quality, peer-reviewed research from preprints. Although
preprints are often later published in peer-reviewed journals, this information
is often missing from preprint servers. To overcome this problem, the
PreprintResolver was developed, which uses four literature databases (DBLP,
SemanticScholar, OpenAlex, and CrossRef / CrossCite) to identify
preprint-publication pairs for the arXiv preprint server. The target audience
focuses on, but is not limited to inexperienced researchers and students,
especially from the field of computer science. The tool is based on a fuzzy
matching of author surnames, titles, and DOIs. Experiments were performed on a
sample of 1,000 arXiv-preprints from the research field of computer science and
without any publication information. With 77.94 %, computer science is highly
affected by missing publication information in arXiv. The results show that the
PreprintResolver was able to resolve 603 out of 1,000 (60.3 %) arXiv-preprints
from the research field of computer science and without any publication
information. All four literature databases contributed to the final result. In
a manual validation, a random sample of 100 resolved preprints was checked. For
all preprints, at least one result is plausible. For nine preprints, more than
one result was identified, three of which are partially invalid. In conclusion
the PreprintResolver is suitable for individual, manually reviewed requests,
but less suitable for bulk requests. The PreprintResolver tool
(https://preprintresolver.eu, Available from 2023-08-01) and source code
(https://gitlab.com/ippolis_wp3/preprint-resolver, Accessed: 2023-07-19) is
available online.
