Dikshan N Shah

Papers

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About

Dikshan N Shah is a researcher in natural language processing (NLP), with a particular focus on low-resource languages and rule-based approaches to text analysis. His most notable contribution is the development of a rule-based system for Named Entity Recognition (NER) in Gujarati, a language with limited computational resources. In his 2018 paper, "Named Entity Recognition from Gujarati Text Using Rule-Based Approach," Shah introduced a method that leverages linguistic rules to identify and classify named entities—such as names, places, and organizations—in Gujarati text. This work, which has garnered 10 citations, addresses a critical gap in NLP for Indic languages, offering a practical solution for information extraction in domains like digital humanities and regional language processing. Shah’s approach demonstrates how rule-based techniques can be effectively applied to languages where annotated datasets are scarce, making his research valuable for scholars working on under-resourced languages. His work stands as a foundational step toward building more robust NLP tools for Gujarati, inspiring further exploration into hybrid models that combine rule-based and machine learning methods.