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Search Engine enhanced with Generative AI

Luigi Federico

Search Engine enhanced with Generative AI.

Rel. Paolo Garza. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2024

Abstract:

E-commerce or website that don’t customize results based on customer behavior and interests may display products that aren’t relevant to the buyer or return zero results. Research shows that 80% of shoppers will abandon a site after a poor search experience. The goal of the project is 1) to study the state of the art of Generative AI applied to this field 2) to design and implement a search engine component that accepts user queries and interacts with a generative AI model 3) to incorporate user feedbacks into the training process for continuously refining and improving its performance.

Relators: Paolo Garza
Academic year: 2023/24
Publication type: Electronic
Number of Pages: 117
Additional Information: Tesi secretata. Fulltext non presente
Subjects:
Corso di laurea: Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering)
Classe di laurea: New organization > Master science > LM-32 - COMPUTER SYSTEMS ENGINEERING
Aziende collaboratrici: DATA Reply S.r.l. con Unico Socio
URI: http://webthesis.biblio.polito.it/id/eprint/30949
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