Identification of research trends in the field of separation processes. Application of epidemiological model, citation analysis, text mining, and technical analysis of the financial markets


Autoria(s): Sitarz, Robert
Data(s)

21/10/2013

21/10/2013

25/10/2013

Resumo

Choice of industrial development options and the relevant allocation of the research funds become more and more difficult because of the increasing R&D costs and pressure for shorter development period. Forecast of the research progress is based on the analysis of the publications activity in the field of interest as well as on the dynamics of its change. Moreover, allocation of funds is hindered by exponential growth in the number of publications and patents. Thematic clusters become more and more difficult to identify, and their evolution hard to follow. The existing approaches of research field structuring and identification of its development are very limited. They do not identify the thematic clusters with adequate precision while the identified trends are often ambiguous. Therefore, there is a clear need to develop methods and tools, which are able to identify developing fields of research. The main objective of this Thesis is to develop tools and methods helping in the identification of the promising research topics in the field of separation processes. Two structuring methods as well as three approaches for identification of the development trends have been proposed. The proposed methods have been applied to the analysis of the research on distillation and filtration. The results show that the developed methods are universal and could be used to study of the various fields of research. The identified thematic clusters and the forecasted trends of their development have been confirmed in almost all tested cases. It proves the universality of the proposed methods. The results allow for identification of the fast-growing scientific fields as well as the topics characterized by stagnant or diminishing research activity.

Identificador

978-952-265-484-7

1456-4491

http://www.doria.fi/handle/10024/93330

URN:ISBN:978-952-265-484-7

Idioma(s)

en

Publicador

Lappeenranta University of Technology

Relação

978-952-265-483-0

Acta Universitatis Lappeenrantaensis

Palavras-Chave #technology forecasting #text mining #knowledge management #trend analysis #distillation #filtration
Tipo

Väitöskirja

Doctoral Dissertation