Generation theory in HR practice: text mining for talent management case

Automation of talent and skills management is becoming an increasingly popular strategic tool in business and government institutions. In this paper, we describe the possible applications of Generation Theory for Human Resource Management in various business and government organizations, briefly introduce the Decision Support System for Talent Management (DSSTM) and present an attempt to classify persons from two different generations based on texts they produce. To cope with this task, we apply Text Mining techniques, namely, LSA-based key term extraction and Word2Vec model for word embeddings. The experiments show promising results.