SubmissionNumber#=%=#176
FinalPaperTitle#=%=#INGEOTEC at SemEval-2024 Task 1: Bag of Words and Transformers
ShortPaperTitle#=%=#
NumberOfPages#=%=#5
CopyrightSigned#=%=#Daniela Moctezuma
JobTitle#==#Professor
Organization#==#Circuito Tecnopolo Norte, No.107 Col. Tecnopolo Pocitos II, 20313 Aguascalientes, Ags. Mexico
Abstract#==#Understanding the meaning of a written message is crucial in solving problems related to Natural Language Processing; the relatedness of two or more messages is a semantic problem tackled with supervised and unsupervised learning. This paper outlines our submissions to the  Semantic Textual Relatedness (STR) challenge at SemEval 2024, which is devoted to evaluating the degree of semantic similarity and relatedness between two sentences across multiple languages. We use two main strategies in our submissions. The first approach is based on the Bag-of-Word scheme, while the second one uses pre-trained Transformers for text representation. We found some attractive results, especially in cases where different models adjust better to certain languages over others.
Author{1}{Firstname}#=%=#Daniela
Author{1}{Lastname}#=%=#Moctezuma
Author{1}{Username}#=%=#dmocteo
Author{1}{Email}#=%=#dmocteo@gmail.com
Author{1}{Affiliation}#=%=#Centrogeo
Author{2}{Firstname}#=%=#Eric Sadit
Author{2}{Lastname}#=%=#Tellez
Author{2}{Username}#=%=#sadit
Author{2}{Email}#=%=#eric.tellez@infotec.mx
Author{2}{Affiliation}#=%=#CONACyT-INFOTEC
Author{3}{Firstname}#=%=#Mario
Author{3}{Lastname}#=%=#Graff
Author{3}{Username}#=%=#mgraffg
Author{3}{Email}#=%=#mario.graff@infotec.mx
Author{3}{Affiliation}#=%=#INFOTEC Centro de Investigación e Innovación en Tecnologías de la Información y Comunicación

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