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.

Amato, F., Boselli, R., Cesarini, M., Mercorio, F., Mezzanzanica, M., Moscato, V., et al. (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. [10.1109/ICOSC.2015.7050852].

Challenge: Processing web texts for classifying job offers

BOSELLI, ROBERTO
Secondo
;
CESARINI, MIRKO;MERCORIO, FABIO;MEZZANZANICA, MARIO;
2015

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.
No
paper
Computer Networks and Communications; Computer Science Applications1707 Computer Vision and Pattern Recognition; Information Systems; Software
English
9th IEEE International Conference on Semantic Computing, IEEE ICSC 2015
9781479979356
2015
Amato, F., Boselli, R., Cesarini, M., Mercorio, F., Mezzanzanica, M., Moscato, V., et al. (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. [10.1109/ICOSC.2015.7050852].
Amato, F; Boselli, R; Cesarini, M; Mercorio, F; Mezzanzanica, M; Moscato, V; Persia, F; Picariello, A
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/84414
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