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Search Engine enhanced with Generative AI

Luigi Federico

Search Engine enhanced with Generative AI.

Rel. Paolo Garza. Politecnico di Torino, UNSPECIFIED, 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: UNSPECIFIED
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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