Enhancing User Experience on Q&A Platforms: Measuring Text Similarity Based on Hybrid CNN-LSTM Model for Efficient Duplicate Question Detection-Reference-Cited by-同舟云学术

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

Published:2024 Issue: Volume:12 Page:34512-34526
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Faseeh Muhammad¹^ORCID,Khan Murad Ali²,Iqbal Naeem³^ORCID,Qayyum Faiza²^ORCID,Mehmood Asif⁴^ORCID,Kim Jungsuk⁴^ORCID

Affiliation:

1. Department of Electronics Engineering, Jeju National University, Jeju-si, Republic of Korea

2. Department of Computer Engineering, Jeju National University, Jeju-si, Republic of Korea

3. School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Belfast, U.K.

4. Department of Biomedical Engineering, College of IT Convergence, Gachon University, Sujeong-gu, Seongnam-si, Republic of Korea

Funder

Ministry of Trade, Industry and Energy and the Korea Institute of Industrial Technology Evaluation and Management (KEIT), in 2023

Gachon University Research Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10414059.pdf?arnumber=10414059

Reference63 articles.

1. Characterization and Prediction of Questions without Accepted Answers on Stack Overflow

2. Duplicate Question Detection With Deep Learning in Stack Overflow

3. Marking Essays Automatically

4. Term weighting scheme for short-text classification: Twitter corpuses

5. Duplicate Question Detection in Question Answer Website using Convolutional Neural Network

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