Author(s): Rakesh Pimplikar, Anuradha Bhamidipaty, Joydeep Mondal, Ankita Gupta, Ruchi Mahindru, Gen Lauer, Radha Ratnaparkhi
Abstract: We present a novel system to generate an enterprise skills taxonomy for an organization. The taxonomy dynamically adapts to the changes in the organizational environment. Changes could be due to acquisition of new skills by the employees, hiring of new employees, attrition of employees, or changes in the focus of the organization’s strategy. Our approach involves crawling millions of public (technical) documents authored by the employees, and combining them with the organization’s internal data (like employee HR data). In the process, skills are extracted and assigned to employees. Our approach doesn’t have the problems of manually curated taxonomies which are difficult to generate and to keep up to date. We also propose an approach to customize the skills taxonomy for the specific enterprise at hand by utilizing a domain specific seed taxonomy. Our system has a lot of potential to impact various workforce related applications such as analyzing expertise gaps and employee development.
Keywords: Named-Entity Recognition; Asymmetric Similarity; Enterprise Skills Taxonomy