What is it about?
This research looks at how scientific papers are related by analyzing their co-citations—when two papers are cited together. Rather than simply counting how often papers are co-cited, this study uses a new method that considers the meaning of the words in the paper titles. By measuring the similarity of the words used, we can gain deeper insights into how related the co-cited papers are, making the analysis more meaningful.
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Why is it important?
This work introduces a new way to improve the analysis of scientific papers by incorporating meaning, not just numbers. By using semantic similarity to measure the relationship between co-cited papers, the study offers a more nuanced approach that could lead to better understanding of research trends and connections. This method is particularly useful in a time where the volume of research is rapidly increasing, and finding meaningful patterns is crucial.
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This page is a summary of: Semantic-driven bibliometric techniques for co-citation analysis, International Journal of Hybrid Intelligent Systems, July 2020, IOS Press,
DOI: 10.3233/his-200288.
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