Adishree R. Ghorpade

About

Adishree R. Ghorpade is a researcher in artificial intelligence and natural language processing, with a particular focus on document classification and neural network architectures. Her most-cited work, "Document Classification using LSTM Neural Network" (2017), has garnered 18 citations and addresses the critical challenge of automatically categorizing the rapidly growing volume of electronic documents. In this influential paper, Ghorpade demonstrates how Long Short-Term Memory (LSTM) networks can effectively learn from labeled data to predict categories for unseen documents, advancing the field of document categorization. Her contributions are especially relevant as organizations increasingly rely on automated systems to manage and organize vast textual datasets. By applying deep learning techniques to traditional classification problems, Ghorpade has helped bridge the gap between classical machine learning and modern neural approaches. Her work serves as a valuable reference for researchers and students exploring sequence-based models for text analysis, highlighting the practical importance of training known labels to predict unknown ones in real-world applications.

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Top Papers

1. 1
   Document Classification using LSTM Neural Network

   18 citations · 2017

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