| Name: | Description: | Size: | Format: | |
|---|---|---|---|---|
| 7.19 MB | Adobe PDF |
Authors
Advisor(s)
Abstract(s)
Esta dissertação aborda a transformação do setor imobiliário com a integração de tecnologias
avançadas, como Inteligência Artificial (IA), Processamento de Linguagem Natural
(NLP) e Modelos de Linguagem de Grande Escala (LLM). O foco é melhorar a experiência
do utilizador na procura por propriedades online, enfrentando o desafio da sobrecarga de
informações nos sites de imobiliárias. A solução proposta visa oferecer uma experiência mais
intuitiva e personalizada, utilizando sugestões inteligentes para antecipar as preferências dos
utilizadores e adaptar as recomendações de propriedades. O estudo explora a eficácia de diferentes
prompts utilizados na interação com LLM e avalia a solução através de indicadores
de satisfação do cliente. O estado da arte destaca a importância da integração de LLM e IA,
comparando sua eficácia com métodos tradicionais de pesquisa. Questões éticas, desafios e
oportunidades associados ao uso de LLM também são discutidos, enfatizando a eficiência de
recursos e a necessidade de um refinamento contínuo dos modelos. A dissertação contribui
para o avanço das aplicações de IA em sistemas imobiliários, proporcionando uma base sólida
para o desenvolvimento de soluções mais eficazes e orientadas ao utilizador.
The dissertation addresses the transformation of the real estate sector with the integration of advanced technologies such as Artificial Intelligence (AI), Natural Language Processing (NLP), and Large Language Models (LLMs). The focus is on enhancing the user experience in online property searches by tackling the challenge of information overload on real estate websites. The proposed solution aims to offer a more intuitive and personalized experience by using intelligent suggestions to anticipate user preferences and adapt property recommendations. The study explores the effectiveness of different prompts used in interactions with LLMs and evaluates the solution through customer satisfaction indicators. The state of the art highlights the importance of integrating LLMs and AI, comparing their effectiveness with traditional search methods. Ethical issues, challenges, and opportunities associated with the use of LLMs are also discussed, emphasizing resource efficiency and the need for continuous model refinement. The dissertation contributes to the advancement of AI applications in real estate systems, providing a solid foundation for developing more effective and user-oriented solutions.
The dissertation addresses the transformation of the real estate sector with the integration of advanced technologies such as Artificial Intelligence (AI), Natural Language Processing (NLP), and Large Language Models (LLMs). The focus is on enhancing the user experience in online property searches by tackling the challenge of information overload on real estate websites. The proposed solution aims to offer a more intuitive and personalized experience by using intelligent suggestions to anticipate user preferences and adapt property recommendations. The study explores the effectiveness of different prompts used in interactions with LLMs and evaluates the solution through customer satisfaction indicators. The state of the art highlights the importance of integrating LLMs and AI, comparing their effectiveness with traditional search methods. Ethical issues, challenges, and opportunities associated with the use of LLMs are also discussed, emphasizing resource efficiency and the need for continuous model refinement. The dissertation contributes to the advancement of AI applications in real estate systems, providing a solid foundation for developing more effective and user-oriented solutions.
Description
Keywords
AI NLP LLM Prompt JSON Imobiliária