@misc{PUB-0026,
  title = {{Hierarchical Classification of OAI Metadata Using the DDC Taxonomy}},
  author = {Waltinger, U. and Mehler, A. and Lösch, M. and Horstmann, W.},
  year = {2011},
  doi = {10.1007/978-3-642-23160-5\_3},
  url = {https://doi.org/10.1007/978-3-642-23160-5\_3},
  abstract = {In the area of digital library services, the access to subject-specific metadata of scholarly
publications is of utmost interest. One of the most prevalent approaches for metadata exchange
is the XML-based Open Archive Initiative (OAI) Protocol for Metadata Harvesting (OAI-PMH).
However, due to its loose requirements regarding metadata content there is no strict standard
for consistent subject indexing specified, which is furthermore needed in the digital library
domain. This contribution addresses the problem of automatic enhancement of OAI metadata by
means of the most widely used universal classification schemes in libraries—the Dewey Decimal
Classification (DDC). To be more specific, we automatically classify scientific documents
according to the DDC taxonomy within three levels using a machine learning-based classifier
that relies solely on OAI metadata records as the document representation. The results show an
asymmetric distribution of documents across the hierarchical structure of the DDC taxonomy and
issues of data sparseness. However, the performance of the classifier shows promising results
on all three levels of the DDC.},
  note = {Waltinger, U., Mehler, A., Lösch, M., \& Horstmann, W. (2011). Hierarchical Classification of OAI Metadata Using the DDC Taxonomy. In R. Bernardi, S. Chambers, B. Gottfried, F. Segond, \& I. Zaihrayeu (Eds.), Lecture Notes in Computer Science: Vol. 6699. Advanced Language Technologies for Digital Libraries (pp. 29–40). Berlin / Heidelberg: Springer.}
}