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2022 SEMEVAL SemEval 2022

WueDevils at SemEval-2022 Task 8: Multilingual News Article Similarity via Pair-Wise Sentence Similarity Matrices

Abstract

AbstractWe present a system that creates pair-wise cosine and arccosine sentence similarity matrices using multilingual sentence embeddings obtained from pre-trained SBERT and Universal Sentence Encoder (USE) models respectively. For each news article sentence, it searches the most similar sentence from the other article and computes an average score. Further, a convolutional neural network calculates a total similarity score for the article pairs on these matrices. Finally, a random forest regressor merges the previous results to a final score that can optionally be extended with a publishing date score.

🌉 Interdisciplinary Bridge — Deep Learning and Machine Learning
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio

Authors

Dirk Wangsadirdja , Felix Heinickel , Simon Trapp , Albin Zehe , Konstantin Kobs , Andreas Hotho

Topics

Machine Learning > Core Methods > Regression Machine Learning > Core Methods > Embedding Learning Deep Learning > Architectures > Neural Networks

Keywords

similarity matrix convolutional neural network random forest sentence embedding multilingual embedding
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