Text Mining at SemEval-2024 Task 1: Evaluating Semantic Textual Relatedness in Low-resource Languages using Various Embedding Methods and Machine Learning Regression Models
Ron Keinan · 2024
In this paper, I describe my submission to the SemEval-2024 contest.I tackled subtask 1 -"Semantic Textual Relatedness for African and Asian Languages".To find the semantic relatedness of sentence pairs, I tackled this task by creating models for nine different languages.I then vectorized the text data using a variety of embedding techniques including doc2vec, tf-idf, Sentence-Transformers, Bert, Roberta, and more, and used 11 traditional machine learning techniques of the regression type for analysis and evaluation.