Placement Connect: An ML-Based Approach to Resume Screening and Placement Drive Optimization
摘要
Placement connect is an online platform that simplifies the placement procedures of educational institutions with a systematic and automated process. It uses machine learning algorithms, namely the k-Nearest Neighbors (KNN) algorithm, to interpret resumes in terms of job descriptions to facilitate accurate matching and shortlisting of students. The system also monitors students’ performance during placement drives, giving systematic and transparent organizational information. With Power BI analysis, Placement Connect provides data insights, facilitating improved decision-making at institutions. 95% accuracy is achieved using the KNN algorithm, higher than that of logistic regression and decision trees, in job-role matching. With this new hassle-free technology, resume mismatching, split drive management, and no central tracking are completely eliminated, leading to a seamless placement process.