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Transforming literature-intensive research processes through text analytics – design, implementation and lessons learned

  • The continuing growth of scientific publications raises the question how research processes can be digitalized and thus realized more productively. Especially in information technology fields, research practice is characterized by a rapidly growing volume of publications. For the search process various information systems exist. However, the analysis of the published content is still a highly manual task. Therefore, we propose a text analytics system that allows a fully digitalized analysis of literature sources. We have realized a prototype by using EBSCO Discovery Service in combination with IBM Watson Explorer and demonstrated the results in real-life research projects. Potential addressees are research institutions, consulting firms, and decision-makers in politics and business practice.

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Author:Frank Bensberg, Gunnar Auth, Christian Czarnecki, Christopher Wörndle
Editor:H. Kemal İlter
Document Type:Conference Proceeding
Year of Completion:2018
Contributing Corporation:Ankara Yıldırım Beyazıt University
Date of the Publication (Server):2022/11/02
Tag:Literature review; Research process; Text analytics; Text mining
Length:9 Seiten
5th International Management Information Systems Conference.
October 24-26 2018, Ankara
Institutes:FH Aachen / Fachbereich Elektrotechnik und Informationstechnik
collections:Open Access
Licence (German):License LogoCreative Commons - Namensnennung