ONTOLOGY BASED CLASSIFICATION AND CLUSTERING OF RESEARCH PROPOSALS AND EXTERNAL RESEARCH REVIEWERS

Authors

  • Preet Kaur Lovely Professional University, Phagwara
  • Richa Sapra Lovely Professional University, Phagwara

DOI:

https://doi.org/10.24297/ijct.v5i1.4386

Keywords:

Ontology-based Text Mining Method, Clustering, Classification, Research Project Selection

Abstract

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.

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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

Issue

Section

Research Articles