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.
Cite
CITATION STYLE
Amato, F., Boselli, R., Cesarini, M., Mercorio, F., Mezzanzanica, M., Moscato, V., … Picariello, A. (2015). Challenge: Processing web texts for classifying job offers. In Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing, IEEE ICSC 2015 (pp. 460–463). Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/ICOSC.2015.7050852
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