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Unsupervise learned word embeddings have seen tremendous success in numerousNatural Language Processing (NLP) tasks in recent years. The main contributionof this paper is to develop a technique called Skill2vec, which applies machinelearning techniques in recruitment to enhance the search strategy to findcandidates possessing the appropriate skills. Skill2vec is a neural networkarchitecture inspired by Word2vec, developed by Mikolov et al. in 2013. Ittransforms skills to new vector space, which has the characteristics ofcalculation and presents skills relationships. We conducted an experimentevaluation manually by a recruitment company's domain experts to demonstratethe effectiveness of our approach.

Skill2vec: Machine Learning Approach for Determining the Relevant Skills from Job Description