Web Scraping and Naïve Bayes Classification for Job Search Engine

Abstract

Many organisations (government of non-government) use websites to share information of new recruitment for the workers. This information overflows on thousands of sites with various attributes and criteria. However, this availability forms a complex puzzle in the selection process and lead to inefficient runtime. This study proposes a simple method for job searching simplification through a construction and collaboration of web scraping technique and classification using Naïve Bayes on search engine. This study is resulting an effective and efficient application for users to seek a potential job that fit in with their interests.