Rekha Vijayvergia
Papers
1
Total Citations
4
H-Index
1
About
Dr. Rekha Vijayvergia is a researcher specializing in Natural Language Processing (NLP) and Artificial Intelligence, with a particular focus on Named Entity Recognition (NER) for Indian languages. Her work addresses the critical challenge of adapting NER—a key NLP application that identifies entities like persons, organizations, and locations—to the linguistic diversity and complexity of Indian languages. Her most cited paper, "A Survey on Various Approaches Used in Named Entity Recognition for Indian Languages" (2022), with 4 citations, provides a comprehensive overview of machine learning and AI techniques for this domain, serving as a foundational resource for researchers working on multilingual NLP. Dr. Vijayvergia’s contributions highlight the importance of bridging AI advancements with regional language processing, enabling better information extraction and accessibility. Her research is particularly valuable for developing tools that support India’s multilingual digital ecosystem, impacting fields from information retrieval to cultural heritage preservation. By synthesizing existing approaches and identifying gaps, she has helped pave the way for more robust NER systems in underrepresented languages, making her work a notable step toward inclusive AI technologies.
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Top Papers
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