Εξατομικευμένη εφαρμογή ευρέσεως θέσεων εργασίας
Personalized application for finding job positions

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Keywords
Εφαρμογή Android ; Εύρεση εργασίας ; Προσωποποιημένες προτάσεις ; Αυτόματη σύσταση θέσεων εργασίαςAbstract
In this thesis the application “JobFinder”, a personalized job search application on Android, was developed. Its purpose is to automate the process of job and personnel search for the convenience of employees and employers. The application is implemented in Java and developed in Android Studio. It leverages the Cloud services Firebase Realtime Database, Firebase Authentication and Firebase Storage to manage user information. It also integrates the Open Street Map for the location selection process.
Users are divided into two categories: employees and companies. For the employee category, various actions are allowed such as entering and editing their resume data. Based on this data, an automated job search can be performed. Otherwise, there is also the option of manual job search using filters. At the same time, the functions of saving new search preferences, applying to job advertisements and monitoring their status, and receiving notifications of new positions or positive responses to their applications are provided.
For the category of companies, similar to employees, there is a possibility to complete and edit their profile. It is also possible to post job advertisements and manage applications received from interested employees. This management includes the possibility of viewing only those candidates who match the requirements of each advertisement and accepting or rejecting candidates. In terms of informing companies, notifications are received when interest is expressed by employees for an advertisement.
The automation of the job search process is the main feature of the application. It allows employees to receive personalized ad suggestions, thus reducing the time and effort of finding suitable jobs. The use of Firebase services ensures that data is stored and instantly updated in real-time, while the application's User-Interface (UI) is simple to use and aids the overall user experience.
The app can significantly improve the job search and recruitment process between employees and employers. Future improvements could include incorporating machine learning algorithms for even more accurate job recommendations and support for operating offline.