SubmissionNumber#=%=#142
FinalPaperTitle#=%=#Pinealai at SemEval-2024 Task 1: Exploring Semantic Relatedness Prediction using Syntactic, TF-IDF, and Distance-Based Features.
ShortPaperTitle#=%=#
NumberOfPages#=%=#5
CopyrightSigned#=%=#ANVI ALEX EPONON
JobTitle#==#
Organization#==#Centro de Investigación en Computación CIC - National Polytechnic Institute IPN811229H26. Miguel Othón de Mendizábal S/N, La Escalera, Gustavo A. Madero, Mexico City, 07320, Mexico.
Abstract#==#The central aim of this experiment is to establish a system proficient in predicting semantic relatedness between pairs of English texts. Additionally, the study seeks to delve into diverse features capable of enhancing the ability of models to identify semantic relatedness within given sentences.  Several strategies have been used that combine TF-IDF, syntactic features, and similarity measures to train machine learning to predict semantic relatedness between pairs of sentences. The results obtained were above the baseline with an approximate Spearman score of 0.84.
Author{1}{Firstname}#=%=#Alex Anvi
Author{1}{Lastname}#=%=#Eponon
Author{1}{Username}#=%=#anvi_x
Author{1}{Email}#=%=#epononanvialex@gmail.com
Author{1}{Affiliation}#=%=#nstituto Politécnico Nacional (IPN), Centro de Investigación en Computación (CIC),
Author{2}{Firstname}#=%=#Luis Israel
Author{2}{Lastname}#=%=#Ramos Perez
Author{2}{Username}#=%=#luisramos07
Author{2}{Email}#=%=#lramos2020@cic.ipn.mx
Author{2}{Affiliation}#=%=#Instituto Politecnico Nacional (IPN) Centro de Investigacion en Computacion (CIC)

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