Enhancing Textual Relatedness Assessment with Combined Transformers-Embedding Similarity Techniques and Machine Learning Regressors-Reference-Cited by-同舟云学术

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Enhancing Textual Relatedness Assessment with Combined Transformers-Embedding Similarity Techniques and Machine Learning Regressors

Published:2023-07-15 Issue: Volume: Page:
ISSN:
Container-title:2023 Intelligent Methods, Systems, and Applications (IMSA)
language:
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Author:

Hany Mena¹,Saeed Mostafa Mohamed¹,Reda Waly Rana¹,Nagib Abdelrahman Ezzeldin¹,Gomaa Wael H.²

Affiliation:

1. University for Modern Sciences and Arts,Faculty of Computer Science,Cairo,Egypt

2. Beni-Suef University Faculty of Computer Science, MSA University,Faculty of Computer and Artificial Intelligence

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10217215/10217348/10217726.pdf?arnumber=10217726

Reference19 articles.

1. Challenging the Boundaries of Unsupervised Learning for Semantic Similarity

2. Sentence-t5: Scalable sentence encoders from pre-trained text-to-text models;ni;CoRR,2021

3. Mean Square Error

4. Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

5. Siamese Recurrent Architectures for Learning Sentence Similarity

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Advancements in Arabic Tweets Sarcasm Detection & Sentiment Analysis with Fine-Tuned Models;2024 Intelligent Methods, Systems, and Applications (IMSA);2024-07-13

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