Desarrollo de una taxonomía específica de dominio y aplicación a un motor de búsqueda
The main goal of this project is to develop a taxonomy and an apply it to optimize the search engine of an app for mothers and health professionals that facilitates breastfeeding. The app allows mothers to create a profile for them and their babies to keep track of breastfeeding and includes a knowl...
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| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universitat Oberta de Catalunya (UOC) |
| Repositorio: | O2, repositorio institucional de la UOC |
| OAI Identifier: | oai:openaccess.uoc.edu:10609/147655 |
| Acceso en línea: | http://hdl.handle.net/10609/147655 |
| Access Level: | acceso abierto |
| Palabra clave: | natural language processing taxonomy search engine procesamiento del lenguaje natural taxonomía motor de búsqueda processament del llenguatge natural taxonomia motor de cerca Web search engines -- TFM Cercadors d'Internet -- TFM Buscadores de Internet -- TFM |
| Sumario: | The main goal of this project is to develop a taxonomy and an apply it to optimize the search engine of an app for mothers and health professionals that facilitates breastfeeding. The app allows mothers to create a profile for them and their babies to keep track of breastfeeding and includes a knowledge database with thousands of articles organized by specific topics that they can check to clarify their doubts. The app also has a search engine by keyword and a chatroom. Users can use the chatroom to send questions to the team of breastfeeding consultants when they don’t find the answer in the articles. The use of NLP models combined with the taxonomy on the searches and questions posted in the chatroom, will improve the accuracy on the search results and answers, and will reduce the time consultants devote to manually answer questions through the chat, which currently is the main bottleneck for scalability. For the definition of the taxonomy, all the knowledge present in the app, all the questions made by the users and the answers received, the most frequently searched concepts and the main topics identified will be used. Once created, an application to validate it will be developed. |
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