Methodological Demonstration of a Text Analytics Approach to Country Logistics System Assessments

Publikation: Bidrag til bog/antologi/rapportBidrag til bog/antologiForskningpeer review

Resumé

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.
OriginalsprogEngelsk
TitelDynamics in Logistics : Proceedings of the 5th International Conference LDIC, 2016 Bremen, Germany
RedaktørerMichael Freitag, Herbert Kotzab, Jürgen Pannek
Udgivelses stedCham
ForlagSpringer
Publikationsdato2017
Sider119-129
Kapitel11
ISBN (Trykt)9783319451169
ISBN (Elektronisk)9783319451176
DOI
StatusUdgivet - 2017
BegivenhedThe 5th International Conference on Dynamics in Logistics. LDIC 2016 - Bremen, Tyskland
Varighed: 22 feb. 201625 feb. 2016
Konferencens nummer: 5
http://www.ldic-conference.org/

Konference

KonferenceThe 5th International Conference on Dynamics in Logistics. LDIC 2016
Nummer5
LandTyskland
ByBremen
Periode22/02/201625/02/2016
Internetadresse
NavnLecture Notes in Logistics
ISSN2194-8917

Emneord

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

Citer dette

Kinra, A., Mukkamala, R. R., & Vatrapu, R. (2017). Methodological Demonstration of a Text Analytics Approach to Country Logistics System Assessments. I M. Freitag, H. Kotzab, & J. Pannek (red.), Dynamics in Logistics: Proceedings of the 5th International Conference LDIC, 2016 Bremen, Germany (s. 119-129). Cham: Springer. Lecture Notes in Logistics https://doi.org/10.1007/978-3-319-45117-6_11
Kinra, Aseem ; Mukkamala, Raghava Rao ; Vatrapu, Ravi. / Methodological Demonstration of a Text Analytics Approach to Country Logistics System Assessments. Dynamics in Logistics: Proceedings of the 5th International Conference LDIC, 2016 Bremen, Germany. red. / Michael Freitag ; Herbert Kotzab ; Jürgen Pannek. Cham : Springer, 2017. s. 119-129 (Lecture Notes in Logistics).
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abstract = "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.",
keywords = "Logistics, Transport system evaluation, Big data analytics, Data mining, Text mining, Machine learning, Logistics, Transport system evaluation, Big data analytics, Data mining, Text mining, Machine learning",
author = "Aseem Kinra and Mukkamala, {Raghava Rao} and Ravi Vatrapu",
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Kinra, A, Mukkamala, RR & Vatrapu, R 2017, Methodological Demonstration of a Text Analytics Approach to Country Logistics System Assessments. i M Freitag, H Kotzab & J Pannek (red), Dynamics in Logistics: Proceedings of the 5th International Conference LDIC, 2016 Bremen, Germany. Springer, Cham, Lecture Notes in Logistics, s. 119-129, The 5th International Conference on Dynamics in Logistics. LDIC 2016, Bremen, Tyskland, 22/02/2016. https://doi.org/10.1007/978-3-319-45117-6_11

Methodological Demonstration of a Text Analytics Approach to Country Logistics System Assessments. / Kinra, Aseem; Mukkamala, Raghava Rao; Vatrapu, Ravi.

Dynamics in Logistics: Proceedings of the 5th International Conference LDIC, 2016 Bremen, Germany. red. / Michael Freitag; Herbert Kotzab; Jürgen Pannek. Cham : Springer, 2017. s. 119-129 (Lecture Notes in Logistics).

Publikation: Bidrag til bog/antologi/rapportBidrag til bog/antologiForskningpeer review

TY - CHAP

T1 - Methodological Demonstration of a Text Analytics Approach to Country Logistics System Assessments

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N2 - 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.

AB - 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.

KW - Logistics

KW - Transport system evaluation

KW - Big data analytics

KW - Data mining

KW - Text mining

KW - Machine learning

KW - Logistics

KW - Transport system evaluation

KW - Big data analytics

KW - Data mining

KW - Text mining

KW - Machine learning

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Kinra A, Mukkamala RR, Vatrapu R. Methodological Demonstration of a Text Analytics Approach to Country Logistics System Assessments. I Freitag M, Kotzab H, Pannek J, red., Dynamics in Logistics: Proceedings of the 5th International Conference LDIC, 2016 Bremen, Germany. Cham: Springer. 2017. s. 119-129. (Lecture Notes in Logistics). https://doi.org/10.1007/978-3-319-45117-6_11