Linkly

Linkly (Our fyp Project) is an Artificial Intelligence based recommendation engine for job seekers which guides them on what could be their desired domain and recommend jobs related to that. We at linkly are also connecting job seekers with the people from whom they can get referrals too really easi

Project Title

Linkly

Project Area of Specialization

Artificial Intelligence

Project Summary

Linkly (Our fyp Project) is an Artificial Intelligence based recommendation engine for job seekers which guides them on what could be their desired domain and recommend jobs related to that. We at linkly are also connecting job seekers with the people from whom they can get referrals too really easily.

Linkly has hundreds of jobs being scrapped only regular basis from different job posting platforms such as indeed, rozee.pk, timesjob, jobsdotcom. It gathers the top jobs in the industry and recommends them to potential recommended users.

The Ai engine examines the user from getting his resume or skills and recommends how much his skills are reliable and competitive to the recent industry and on the basis of them, it shows job seekers the best jobs from top job posting sites.

If a job seeker clicks on any job he will also be recommended to people from which he can get referrals for the job these people be his university alumni who are working at the same company.

The Linkly is based upon most trending stems Cloud Computing, Ai, and web development using python, vuejs, was, docker as tech stacks.

Project Objectives

• Jobs of specific industry will be recommended to jobseeker according to her/his skills. 

• Job seeker can connect with alumni of that company. 

• Job scraper will scrape jobs from different job posting websites so that jobseeker can apply for the jobs. 

• Alumni scraper will scrape alumni profiles from different professional platform so the jobseeker can connect with alumni of that company in which he/she is interested to apply for job. 

Project Implementation Method

We will be using agile methodologies to increment all the modules linearly. We will first work on web crawlers as to fetch data from target websites, creating them independent from other modules to scrape data. There are two web scrappers which are job scrapper which is used to scrap data from job posting platforms and second is used to scrap alumni data from professional platform, Resume parsing is used to extract skills, education and experience. We will be using natural language processing in order to organize and extract data which is obtained from resume. We will be using data of multiple jobs to train the model to recommend specific jobs related to a specific domain. Then we will be designing the database of the system and carrying out tests with creating dependencies of each table with the other. Tests being passed the user authentication system will be then created which will allow registration of jobseeker.  

We are going to move along incremental approach as to develop features and keep incrementing them once they are tested with all the dependencies to ensure there are no bugs created in the process. We will start combining them, first, we will combine the web application with the web crawler, by creating an API to accept data, which would then further go forward to the integration of the recommendation system to allow job seekers to get the benefit from the main feature of the system. 

Benefits of the Project

- Recommend the best domain in the industry on the basis of skills using an AI-based most efficient model considering the latest industry trends.

- Recommend the best jobs from top trending companies to jobseekers from top job posting platforms.

- Make it easy to get referrals on the basis of recommended alumni.

Technical Details of Final Deliverable

Scrapers:

The role of scrapers is to scrape jobs from different job posting platforms. These scrapers are scheduled on the cloud in Docker containers and automatically run constantly and update jobs in the linkly database. 

AI Engine:

Ai engine is trained using BERT algorithm which tells what could be the ideal domains for the job seeker. The data for the Ai model is being scrapped from indeed.com and our model is trained on it as indeed is the best job posting platform in the world.

Backend:

We have a really strong backend coded on Django python which manages all the data communication and manipulation of the data including rest apis.

Frontend:

The front is coded on the world's lightest frontend Vuejs framework which communicates with the backend Django server and shows a pleasing and approaching UI to the user.

Technologies used: 

Python, Django, flask, TensorFlow, javascript, vuejs, docker, selenium, beautiful soup, AWS.

Final Deliverable of the Project

Software System

Core Industry

IT

Other Industries

Core Technology

Artificial Intelligence(AI)

Other Technologies

Sustainable Development Goals

Industry, Innovation and Infrastructure

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com