Naslov
Information Extraction from Free-Form CV Documents in Multiple Languages

Autori
Vukadin, Davor ; Kurdija, Adrian Satja ; Delač, Goran ; Šilić, Marin

Izvornik
IEEE access (2169-3536) 9 (2021); 84559-84575

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Information retrieval ; Natural language processing ; Text analysis ; Recurrent neural networks ; CV parsing

Sažetak
This paper proposes two natural language processing models for extracting useful information from multilingual, unstructured (free form) CV documents. The model identifies the relevant document sections (personal information, education, employment, etc.) and the corresponding specific information at the lower hierarchy level (names, addresses, roles, skill competences, etc.). Our approach employs the transformer architecture and its multilingual implementation of the encoder part in the form of the BERT language model. The models are trained and tested on a large, manually annotated CV dataset, achieving high scores on standard accuracy measures. The proposed models exhibit important properties of end-to-end training and interpretability, which was investigated by visualizing the model attention and its vector representations.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

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