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Hesam Mashhadi Mohammad
Visual analytics for job candidates.
Rel. Valentina Gatteschi. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2023
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Abstract: |
The hiring process could be complicated and result in wrong decisions if only the raw data is available to the people responsible for assessing potential new employees. A more efficient and organized way for hiring managers to evaluate job applicants is using data visualization tools to improve the hiring process experience, leading to more reliable results. This work uses web application technologies and data visualization tools to present job applicants' information visually and interactively. Web applications allow consumers to access and interact with services and information on the internet via a web browser, which has become increasingly crucial in today's digital landscape. Aside from being simple to access from anywhere with an internet connection, they also have fewer infrastructure costs than traditional desktop apps and better scalability to handle big user bases. The system's design uses several visualization techniques, including graphs and charts, to display information on applicants' skills, work experience, education, and other factors. A new feature in this application lets job applicants be compared with the team members already working in the company. This way, the hiring manager can determine how each candidate will fit into the team. Using this web application has the advantages of decreasing the time and effort needed to search through resumes and improving the effectiveness and efficiency of the hiring process. This project uses the latest web application technologies, including Reactjs, Expressjs, and REST API. |
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Relatori: | Valentina Gatteschi |
Anno accademico: | 2022/23 |
Tipo di pubblicazione: | Elettronica |
Numero di pagine: | 67 |
Soggetti: | |
Corso di laurea: | Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering) |
Classe di laurea: | Nuovo ordinamento > Laurea magistrale > LM-32 - INGEGNERIA INFORMATICA |
Aziende collaboratrici: | NON SPECIFICATO |
URI: | http://webthesis.biblio.polito.it/id/eprint/26845 |
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