Special Issue "Combining bibliometrics and information retrieval" in Scientometrics published

Mayr-Schlegel, Philipp Philipp.Mayr-Schlegel at GESIS.ORG
Fri Feb 20 05:37:05 EST 2015

Dear colleagues,

the Special Issue "Combining bibliometrics and information retrieval" will appear in the March issue of Scientometrics. Here is the link to the Springer system http://link.springer.com/journal/11192/102/3/page/2.
Below you will find the bibliographic information of the editorial and the eight full papers. Please distribute the information about this special issue to interested colleagues. Our thanks go to all authors and reviewers who have contributed.


Mayr, P., & Scharnhorst, A. (2015). Scientometrics and Information Retrieval - weak-links revitalized. Scientometrics, 102(3), 2193-2199. doi:10.1007/s11192-014-1484-3

Full papers:

Wolfram, D. (2015). The Symbiotic Relationship Between Information Retrieval and Informetrics. Scientometrics, 102(3), 2201-2214. doi:10.1007/s11192-014-1479-0

Glänzel, W. (2015). Bibliometrics-aided retrieval - where information retrieval meets scientometrics. Scientometrics, 102(3), 2215-2222. doi:10.1007/s11192-014-1480-7

Zitt, M. (2015). Meso-level retrieval: IR-bibliometrics interplay and hybrid citation-words methods in scientific fields delineation. Scientometrics, 102(3), 2223-2245. doi:10.1007/s11192-014-1482-5

Bar-Ilan, J., & Levene, M. (2015). The hw-rank: An h-index variant for ranking web pages. Scientometrics, 102(3), 2247-2253. doi:10.1007/s11192-014-1477-2

Karlsson, A., Hammarfelt, B., Steinhauer, H. J., Falkman, G., Olson, N., Nelhans, G., & Nolin, J. (2015). Modeling uncertainty in bibliometrics and information retrieval: an information fusion approach. Scientometrics, 102(3), 2255-2274. doi:10.1007/s11192-014-1481-6

White, H. D. (2015). Co-cited Author Retrieval and Relevance Theory: Examples from the Humanities. Scientometrics, 102(3), 2275-2299. doi:10.1007/s11192-014-1483-4

Abbasi, M. K., & Frommholz, I. (2015). Cluster-based Polyrepresentation as Science Modelling Approach for Information Retrieval. Scientometrics, 102(3), 2301-2322. doi:10.1007/s11192-014-1478-1

Mutschke, P., & Mayr, P. (2015). Science Models for Search. A Study on Combining Scholarly Information Retrieval and Scientometrics. Scientometrics, 102(3), 2323-2345. doi:10.1007/s11192-014-1485-2
Best, Philipp

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Dr. Philipp Mayr
Team Leader
GESIS - Leibniz Institute for the Social Sciences
Unter Sachsenhausen 6-8,  D-50667 Köln, Germany
Tel: + 49 (0) 221 / 476 94 -533
Email: philipp.mayr at gesis.org
Web: http://www.gesis.org

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