Abstract:
The entire findings of my proposal, "AI-Driven Job Recommendation System for Underprivileged Communities in Bangladesh," may be read here. This article covers all of the procedures involved in turning the concept into a working website. In this project, there have one module: User modules. This project introduces a new smartphone application that uses artificial intelligence to deliver individualized career recommendations to Bangladesh's poor areas. The system, built in Java and powered by a large dataset, includes secure user authentication capabilities such as login, registration, and password recovery. Dataset contains almost 3761 data and features like: “experience_level, salary, company_size, age, company_name”, etc are columns. For user’s authentication use SQLite database. Users may utilize the thorough job search option to learn more about potential possibilities, while the AI-powered recommendation search engine examines user inputs to provide personalized job ideas. Furthermore, the program features a multilingual interface that enables for easy switching between English and Bangla, making it accessible to a wide range of users. Overall, this approach seeks to close the employment gap by linking disadvantaged job searchers with suitable work opportunities, promoting socioeconomic empowerment and progress in the region. From idea to execution, the research examines every aspect of mobile application development, including architecture, user interface design, and technologies used. The user interface was built with Java XML, while the backend was built with Python AI and Java. To set up our system application, no expensive software or computer components are required; all you need is a standard desktop computer and Internet access.
