robustrao: An Extended Rao-Stirling Diversity Index to Handle Missing Data

Authors: 
Maria del Carmen Calatrava Moreno
Thomas Auzinger
Type: 
Report
Proceedings: 
Publisher: 
Pages: 
ISBN: 
Year: 
2016
Abstract: 
A collection of functions to compute the Rao-Stirling diversity index (Porter and Rafols, 2009) <doi:10.1007/s11192-008-2197-2> and its extension to acknowledge missing data (i.e., uncategorized references) by calculating its interval of uncertainty using mathematical optimization as proposed in Calatrava et al. (2016) <doi:10.1007/s11192-016-1842-4>. The Rao-Stirling diversity index is a well-established bibliometric indicator to measure the interdisciplinarity of scientific publications. Apart from the obligatory dataset of publications with their respective references and a taxonomy of disciplines that categorizes references as well as a measure of similarity between the disciplines, the Rao-Stirling diversity index requires a complete categorization of all references of a publication into disciplines. Thus, it fails for a incomplete categorization; in this case, the robust extension has to be used, which encodes the uncertainty caused by missing bibliographic data as an uncertainty interval.
TU Focus: 
Information and Communication Technology
Reference: 

M. Calatrava Moreno, T. Auzinger:
"robustrao: An Extended Rao-Stirling Diversity Index to Handle Missing Data";
2016.

Zusätzliche Informationen

Last changed: 
25.07.2016 11:58:52
TU Id: 
250473
Accepted: 
Accepted
Invited: 
Department Focus: 
Business Informatics
Abstract German: 
Author List: 
M. Calatrava Moreno, T. Auzinger