Harshad Bhadka
Papers
2
Total Citations
22
H-Index
2
About
Harshad Bhadka is a researcher specializing in Natural Language Processing (NLP), with a focused expertise in Named Entity Recognition (NER) for Indian languages. His work addresses the critical challenge of automated information extraction from low-resource languages, particularly Gujarati. Bhadka’s major contributions include developing rule-based approaches for NER in Gujarati text, a foundational step for advancing NLP applications in regional Indian languages. His survey paper on NER techniques for Indian languages (12 citations) provides a comprehensive overview of methodologies, highlighting the importance of NER in fields ranging from artificial intelligence to bioinformatics. His subsequent work on Gujarati NER (10 citations) demonstrates practical implementation, offering a rule-based framework that improves text processing accuracy for this under-resourced language. These contributions are vital for enabling automated text analysis, information retrieval, and AI-driven tools in multilingual contexts. Bhadka’s research underscores the growing need for language-specific NLP solutions, making him a notable figure in the advancement of Indian language processing.
Research Focus
Key Achievements
Top Papers
- 1
- 2Named Entity Recognition from Gujarati Text Using Rule-Based Approach10 citations · 2018