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Harnessing the Magic of Regular Expressions: Transforming Citations into Harvard Referencing Style

P.G. Naik, R.S. Kamath, S.S. Jamsandekar, G.R. Naik

Abstract


Current work is centred on the conversion of citations into the Harvard referencing style using regular expressions for pattern recognition. A conceptual model has been devised for this conversion process, and it has been implemented in Python. The ChatGPT API is utilized within Python to cleanse and transform the text into the desired format. Subsequently, regular expressions have been crafted to locate and convert elements such as volume numbers, issue numbers, page numbers, publication years, and author names. Importantly, this model has been designed with flexibility in mind, making it adaptable to future changes in citation styles. It can be easily customized by adjusting the regular expressions to accommodate modifications in any of these components. The research is augmented to find the missing components from the citations such as volume, issue, page no and year from the converted citations which are persisted in a file for future use. The research forms the basis for advancing the field of citation conversion and offers potential solutions to streamline the referencing process for academic and scholarly work.


Keywords


Citation conversion, Harvard referencing style, regular expressions, referencing styles, regular expressions

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References


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