An Automated Candidate Selection System using Bangla Language Processing

• Gensim
• Word2Vec Embedding
• Cosine Similarity
• Bangla Language Processing

Presented at the 3rd INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING & OPTIMIZATION 2020. Available Online at Advances in Intelligent Systems and Computing, Springer

Recruiting or selecting the right candidates from a vast pool of candidates has always been a fundamental issue in Bangladesh as far as employers are concerned. In the case of candidate recruitment, different government organizations, nowadays, ask the applicants to submit their applications or resumes written in Bengali in the form of electronic documents. Matching the skills with the requirements and choosing the best candidates manually from all the resumes written in Bengali is very difficult and time-consuming. To make the recruitment process more comfortable, we have developed an automated candidate selection system. First, it takes the CVs (written in Bengali) of candidates and the employer’s requirements as input. It extracts information from the candidate’s CV using Bangla Language Processing (BLP) and Word2Vec embedding. Then, it generates an average cosine similarity score for each CV. Finally, it ranks the candidates according to the average cosine similarity scores and returns the dominant candidate’s list.