Challenge: Processing web texts for classifying job offers

Abstract

Today the Web represents a rich source of labour market data for both public and private operators, as a growing number of job offers are advertised through Web portals and services. In this paper we apply and compare several techniques, namely explicit-rules, machine learning, and LDA-based algorithms to classify a real dataset of Web job offers collected from 12 heterogeneous sources against a standard classification system of occupations.