ONTOLOGY BASED CLASSIFICATION AND CLUSTERING OF RESEARCH PROPOSALS AND EXTERNAL RESEARCH REVIEWERS
DOI:
https://doi.org/10.24297/ijct.v5i1.4386Keywords:
Ontology-based Text Mining Method, Clustering, Classification, Research Project SelectionAbstract
With the rapid development of research work in projects, research project selection is a necessary task for the research funding agencies. It is common to group the large number of research proposals, received by the research funding agencies. Based on their similarities in Research Discipline areas. The grouped Proposals are then assign to the appropriate Research experts for peer-review. In current methods, which are manual based, proposals assigned to experts may not have adequate knowledge about all discipline areas. In this paper, Ontology-based Text Mining Method is presented to classify Research Project Proposals, as well as External Research Reviewers and then group them based on their research discipline areas and assign the particular research proposal group to the appropriate reviewer group. This approach provides an efficient and effective way for the selection of research project proposals with the increasing number of research proposals and reviewers.Downloads
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Published
2013-06-23
How to Cite
Kaur, P., & Sapra, R. (2013). ONTOLOGY BASED CLASSIFICATION AND CLUSTERING OF RESEARCH PROPOSALS AND EXTERNAL RESEARCH REVIEWERS. INTERNATIONAL JOURNAL OF COMPUTERS &Amp; TECHNOLOGY, 5(1), 49–53. https://doi.org/10.24297/ijct.v5i1.4386
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Research Articles