Big Data and Machine Learning in Government Projects: Expert Evaluation Case

Nikita Nikitinsky, Sergey Shashev, Polina Kachurina and Aleksander Bespalov

MPRA Paper from University Library of Munich, Germany

Abstract: In this paper, we present the Expert Hub System, which was designed to help governmental structures find the best experts in different areas of expertise for better reviewing of the incoming grant proposals. In order to define the areas of expertise with topic modeling and clustering, and then to relate experts to corresponding areas of expertise and rank them according to their proficiency in certain areas of expertise, the Expert Hub approach uses the data from the Directorate of Science and Technology Programmes. Furthermore, the paper discusses the use of Big Data and Machine Learning in the Russian government project.

Keywords: government project; Big Data; Machine Learning; expert evaluation; clustering (search for similar items in EconPapers)
JEL-codes: C55 O38 (search for similar items in EconPapers)
Date: 2016-07-18
New Economics Papers: this item is included in nep-big, nep-cis, nep-cmp, nep-pay and nep-ppm
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/82865/1/project2.pdf original version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:82865

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().