PUBLICATION
Applying Predictive Analytics on Research Information to Enhance Funding Discovery and Strengthen Collaboration in Project Proposals
Type
Conference Paper
Year
2021
Authors
Research Area
Intelligent Information Management
Event
21th International Conference on Web Engineering
Published in
Proceedings of the 21th International Conference on Web Engineering
ISBN/ISSN
978-3-030-74296-6
Download
Abstract
In academic and industrial research, writing a project proposal is one of the essential but time-consuming activities. Nevertheless, most proposals end in rejection. Moreover, research funding is getting more competitive these days. Funding agencies are increasingly looking for more extensive and more interdisciplinary research proposals. To increase the funding success rate, this Ph.D. project focuses on three open challenges: poor data quality, inefficient funding discovery, and ineffective collaborative team building. We envision a Predictive Analytics-based approach that involves analyzing research information and using statistical and machine learning models that can assure data quality, increase funding discovery efficiency and the effectiveness of collaboration building. Accordingly, the goal of this Ph.D. project is to support decision-making process to maximize the funding success rates of universities.
Reference
Hai, Dang V. N.; Langer, André; Gaedke, Martin: Applying Predictive Analytics on Research Information to Enhance Funding Discovery and Strengthen Collaboration in Project Proposals. Proceedings of the 21th International Conference on Web Engineering, 2021.
