Exploration maschineller Verfahren zur Entwicklung eines methodischen Frameworks zur Evaluierung wissenschaftlicher Texte im Forschungsmanagement

Matthias Baumgart

ISBN 10: 3961002037 / ISBN 13: 9783961002030

Published by Universitätsverlag Chemnitz, 2024

About this Item

Exploration maschineller Verfahren zur Entwicklung eines methodischen Frameworks zur Evaluierung wissenschaftlicher Texte im Forschungsmanagement | Matthias Baumgart | Taschenbuch | 488 S. | Deutsch | 2024 | Universitätsverlag Chemnitz | EAN 9783961002030 | Verantwortliche Person für die EU: Universitätsverlag Chemnitz, Straße der Nationen 33, 09111 Chemnitz, uni-verlag[at]bibliothek[dot]tu-chemnitz[dot]de | Anbieter: preigu.

Seller Inventory # 128665911

Bibliographic Details

• Title: Exploration maschineller Verfahren zur Entwicklung eines methodischen Frameworks zur Evaluierung wissenschaftlicher Texte im Forschungsmanagement
• Publisher: Universitätsverlag Chemnitz
• Publication Date: 2024
• Language: German
• ISBN 10: 3961002037
• ISBN 13: 9783961002030
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 28W x 148H x 210D millimeters 28 millimeters width by 148 millimeters height by 210 millimeters depth
• Weight: 698 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

The complexity of research management at universities and colleges of applied sciences has increased in recent years, both on the part of scholars and at the administrative level. In particular, text creation and processing for research proposals, publications and other scientific documents require considerable effort. At the same time, methods and technologies exist in the areas of information retrieval, machine learning, and semantic technologies suitable for the analysis and evaluation of these texts. This work aims to optimize expenditure in the life cycle of publicly funded research projects. It identifies current developments and technologies to derive criteria for an overall architecture that qualitatively annotates, trains, and evaluates scientific texts. The resulting framework called FELIX serves as a prototypical system for computer-aided assistance for evaluating scientific texts. Data corpora from research proposals and publications have been used for exploratory experiments based on methods of machine learning. FELIX enables the analysis of texts and metadata, classification according to defined criteria and predicting the approval of research applications. The conception and evaluation of FELIX led to scientific and practical implications for optimizing research management.