This work is concerned with classifying Web job advertise- ments against a standard classification system of occupations, by apply- ing and comparing different text classification techniques. As a first step, we evaluated the classification algorithms using a hit/not-hit approach, that is either the prediction is correct or not compared to a gold classi- fication provided by domain experts. Then, we built a distance function on top of the affinity relationship between occupations provided by the classification system. Both the classification scores we computed and the affinity distance employed have allowed a more finely grained evaluation of the classified outcomes, providing to authors useful insights towards the improvement of the classification process.
Amato, F., Boselli, R., Cesarini, M., Mercorio, F., Mezzanzanica, M., Moscato, V., et al. (2015). Classification of web job advertisements: A case study. In In Proceedings SEBD 2015 - The 23rd Italian Symposium on Advanced Database Systems (pp.144-151). Sistemi Evoluti per Basi di Dati (SEBD).
Classification of web job advertisements: A case study
BOSELLI, ROBERTOPrimo
;CESARINI, MIRKOSecondo
;MERCORIO, FABIOPenultimo
;MEZZANZANICA, MARIOUltimo
;
2015
Abstract
This work is concerned with classifying Web job advertise- ments against a standard classification system of occupations, by apply- ing and comparing different text classification techniques. As a first step, we evaluated the classification algorithms using a hit/not-hit approach, that is either the prediction is correct or not compared to a gold classi- fication provided by domain experts. Then, we built a distance function on top of the affinity relationship between occupations provided by the classification system. Both the classification scores we computed and the affinity distance employed have allowed a more finely grained evaluation of the classified outcomes, providing to authors useful insights towards the improvement of the classification process.File | Dimensione | Formato | |
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