A Graph-Based Approach to Skill Extraction from Text

This paper presents a system that performs skill extraction from text documents. It outputs a list of professional skills that are relevant to a given input text. We argue that the system can be practical for hiring and management of personnel in an organization. We make use of the texts and the hyperlink graph of Wikipedia, as well as a list of professional skills obtained from the LinkedIn social network. The system is based on first computing similarities between an input document and the texts of Wikipedia pages and then using a biased, hub-avoiding version of the Spreading Activation algorithm on the Wikipedia graph in order to associate the input document with skills.

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