Enhancing User Experience on Q&A Platforms: Measuring Text Similarity Based on Hybrid CNN-LSTM Model for Efficient Duplicate Question Detection

Enhancing User Experience on Q&A Platforms: Measuring Text Similarity Based on Hybrid CNN-LSTM Model for Efficient Duplicate Question Detection

This research introduces an innovative approach for identifying duplicate questions within the Stack Overflow community, a challenging task in NLP. Leveraging deep learning techniques, our proposed methodology combines Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks to...

Полное описание

Библиографические подробности
Главные авторы: Muhammad Faseeh, Murad Ali Khan, Naeem Iqbal, Faiza Qayyum, Asif Mehmood, Jungsuk Kim
Формат: Статья
Язык:English
Опубликовано: IEEE 2024-01-01
Серии:IEEE Access
Предметы:
Duplicate question identification
stack overflow
deep learning (DL)
word embeddings
natural language processing (NLP)
question-and-answer (QA) platforms
Online-ссылка:https://ieeexplore.ieee.org/document/10414059/

Internet

https://ieeexplore.ieee.org/document/10414059/

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