Tracing best semantic path using co-citation proximity analysis

Abstract

Objective. The objective of this work is to find the best semantic path of research papers that matches the given research publication. This paper elaborates on the finding of continuous research progress analysis from semantic perspective. Methodology. Previous work reported the work progress analysis and the integrated as well as optimized approaches to find the progressive research citations which had carried forward the essence of the base reference paper. In this work, we propose to identify the most useful research papers which are semantically closer to the research context, and lie in the citation path of the base paper. Result. Our data set is generated for the popular paper of Hirsch published in 2005, in which, h-index is proposed. The paper has 5299 direct citations till date and the results of the proposed approach indicate very promising findings in view of measuring scientific research progress. Conclusion. The inference reveals a couple of research papers connected as a path among the citation thread, which have significantly progressed the idea of base research paper into a more elaborate yet related context of research..

Keywords

• Citation mining
• Co-citation mining
• Power graph
• Research progress – Language models
• Semantic analysis