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Challenge: Processing web texts for classifying job offers
Conference proceeding   Peer reviewed

Challenge: Processing web texts for classifying job offers

F Amato, R Boselli, M Cesarini, F Mercorio, M Mezzanzanica, V Moscato, Fabio Persia and A Picariello
Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015), pp.460-463
9th IEEE International Conference on Semantic Computing (ICSC 2015) (Anaheim, CA, 07/02/2015 - 09/02/2015)
2015
DOI: https://doi.org/10.1109/ICOSC.2015.7050852
Handle:
https://hdl.handle.net/10863/10497

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.
url
https://ieeexplore.ieee.org/abstract/document/7050852View

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