Web Scraping and Job Recommender System

Web scraping is the process of autonomously obtaining data from webpages using computer software or tools. It has grown in popularity in recent years because of the volume of data available on the internet and the necessity for organizations and individuals to analyze and utilize this data to get the necessary and important information out of it for further analysis and application. Web scraping, together with automation tools, can create wonders. In this paper, we have focused on the latest web scraping techniques and their applications. One of the ideas is to assist those looking for employment on different firm job portals, which is discussed in this paper. Job tracking and scraping collect data from multiple platforms and are web-based tools that help job searchers locate the ideal job for them based on their categories and organize their job search more effectively. People are always on the lookout for a place where they can get their desired information so that they can easily apply for a job. After the collection of data based on user profile attributes, we recommend their success rate based on previous records and an appropriate machine learning model, and we also suggest what skills they can improve to land that job. Web scraping tools allow us to extract the necessary data from different websites in real time and present it to the user. We have discussed various ways to implement scraping and propose a job algorithm to process the extracted data and make it into meaningful information to help users land the best job.