Praxis Market Drift

• Autor(a) principal: Oliveira, Miguel Morim
• Data de Publicação: 2020
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.22/17006
• topic: Text mining; Unstructured data; Preprocessing; Word frequency; Clustering

Over the last decade, digital data has been growing exponentially. Unstructured data is rapidly outgrowing structured data, and so managing unstructured data is increasing as a challenge for many organisations. Consequently, text mining has been gaining traction as a way to deal with unstructured data. Text mining is a form of data mining that deals with text and is the process of transforming unstructured text into meaningful and actionable information. Praxis is a platform that implements a virtual market for project/internship offers. organisations submit their project/internship offers that become available for search, and students search the platform using keywords that express their interest. Praxis has loads of unexplored data from which they can extract useful information to obtain more insights on their internships market. This dissertation proposes a solution based on text mining techniques, that displays the necessary information to analyse the evolution of users’ interests and internship offers submitted in Praxis, over time.