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DOI

The purpose of this study is to develop and demonstrate a semi-automated text analytics approach for the identification and categorization of information that can be used for country logistics assessments. In this paper, we develop the methodology on a set of documents for 21 countries using machine learning techniques while controlling both for 4 different time periods in the world FDI trends, and the different geographic and economic country affiliations. We report illustrative findings followed by a presentation of the separation of concerns/division of labor between the domain expert and the text analyst. Implications are discussed and future work is outlined.

Publication information

Original languageEnglish
Title of host publicationDynamics in Logistics : Proceedings of the 5th International Conference LDIC, 2016 Bremen, Germany
EditorsMichael Freitag, Herbert Kotzab, Jürgen Pannek
Place of PublicationCham
PublisherSpringer
Publication date2017
Pages119-129
Chapter11
ISBN (print)9783319451169
ISBN (electronic)9783319451176
DOIs
StatePublished - 2017
Event - Bremen, Germany

Conference

ConferenceThe 5th International Conference on Dynamics in Logistics. LDIC 2016
Nummer5
LandGermany
ByBremen
Periode22/02/201625/02/2016
Internetadresse
SeriesLecture Notes in Logistics
ISSN2194-8917

    Keywords

  • Logistics, Transport system evaluation, Big data analytics, Data mining, Text mining, Machine learning

ID: 45294416