Jungyeon Jang
Hanyang University · 情報科学
研究室紹介
Professor Jungyeon Jang's research lab specializes in natural language processing and deep learning, with a focus on advancing text classification techniques through innovative neural network architectures. The lab explores hybrid embedding strategies—particularly the integration of word-level and character-level representations—to enhance the performance and robustness of convolutional neural networks in NLP tasks. Current research emphasizes improving model generalization by capturing both semantic and morphological patterns in text data. The lab also investigates efficient and scalable deep learning frameworks for real-world applications in text understanding and information extraction.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
1Deep learning techniques such as Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) show superior performance in text classification than traditional approaches such as Support Vector Machines (SVMs) and Naive Bayesian approaches. When using CNNs for text classification tasks, word embedding or character embedding is a step to transform words or characters to fixed size vectors before feeding them into convolutional layers. In this paper, we propose a parallel word-level a