Bibliometric-Enhanced Information Retrieval

  • Philipp Mayr
  • Andrea Scharnhorst
  • Birger Larsen
  • Philipp Schaer
  • Peter Mutschke
Conference paper

DOI: 10.1007/978-3-319-06028-6_99

Volume 8416 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Mayr P., Scharnhorst A., Larsen B., Schaer P., Mutschke P. (2014) Bibliometric-Enhanced Information Retrieval. In: de Rijke M. et al. (eds) Advances in Information Retrieval. ECIR 2014. Lecture Notes in Computer Science, vol 8416. Springer, Cham

Abstract

Bibliometric techniques are not yet widely used to enhance retrieval processes in digital libraries, although they offer value-added effects for users. In this workshop we will explore how statistical modelling of scholarship, such as Bradfordizing or network analysis of coauthorship network, can improve retrieval services for specific communities, as well as for large, cross-domain collections. This workshop aims to raise awareness of the missing link between information retrieval (IR) and bibliometrics / scientometrics and to create a common ground for the incorporation of bibliometric-enhanced services into retrieval at the digital library interface.

Keywords

Bibliometrics Informetrics Scientometrics Information Retrieval Digital Libraries 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Philipp Mayr
    • 1
  • Andrea Scharnhorst
    • 1
  • Birger Larsen
    • 1
  • Philipp Schaer
    • 1
  • Peter Mutschke
    • 1
  1. 1.GESIS – Leibniz Institute for the Social SciencesCologneGermany