  Unsupervise learned word embeddings have seen tremendous success in numerous
Natural Language Processing (NLP) tasks in recent years. The main contribution
of this paper is to develop a technique called Skill2vec, which applies machine
learning techniques in recruitment to enhance the search strategy to find
candidates possessing the appropriate skills. Skill2vec is a neural network
architecture inspired by Word2vec, developed by Mikolov et al. in 2013. It
transforms skills to new vector space, which has the characteristics of
calculation and presents skills relationships. We conducted an experiment
evaluation manually by a recruitment company's domain experts to demonstrate
the effectiveness of our approach.
