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Pregled bibliografske jedinice broj: 1090810

Candidate Classification and Skill Recommendation in a CV Recommender System


Kurdija, Adrian Satja; Afrić, Petar; Šikić, Lucija; Plejić, Boris; Šilić, Marin; Delač, Goran; Vladimir, Klemo; Srbljić, Siniša
Candidate Classification and Skill Recommendation in a CV Recommender System // Artificial Intelligence and Mobile Services – AIMS 2020
Honolulu, SAD, 2020. str. 30-44 doi:10.1007/978-3-030-59605-7_3 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


CROSBI ID: 1090810 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Candidate Classification and Skill Recommendation in a CV Recommender System

Autori
Kurdija, Adrian Satja ; Afrić, Petar ; Šikić, Lucija ; Plejić, Boris ; Šilić, Marin ; Delač, Goran ; Vladimir, Klemo ; Srbljić, Siniša

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Artificial Intelligence and Mobile Services – AIMS 2020 / - , 2020, 30-44

Skup
9th International Conference on Artificial Intelligence and Mobile Services – AIMS 2020

Mjesto i datum
Honolulu, SAD, 18-20. 9. 2020

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Recommender systems ; Skill recommendation ; Spectral clustering ; Classification

Sažetak
In this paper, we describe a CV recommender system with a focus on two properties. The first property is the ability to classify candidates into roles based on automatic processing of their CV documents. The second property is the ability to recommend skills to a candidate which are not listed in their CV, but the candidate is likely to have them. Both features are based on skills extraction from a textual CV document. A spectral skill clustering is precomputed for the purpose of candidate classification, while skill recommendation is based on various similarity-based strategies. Experimental results include both automatic experiments and an empirical study, both of which demonstrate the effectiveness of the presented methods.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo



POVEZANOST RADA


Projekti:
IP-2018-01-6423 - Pouzdani kompozitni primjenski sustavi zasnovani na web uslugama (RELS) (Srbljić, Siniša, HRZZ - 2018-01) ( POIROT)

Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb

Citiraj ovu publikaciju

Kurdija, Adrian Satja; Afrić, Petar; Šikić, Lucija; Plejić, Boris; Šilić, Marin; Delač, Goran; Vladimir, Klemo; Srbljić, Siniša
Candidate Classification and Skill Recommendation in a CV Recommender System // Artificial Intelligence and Mobile Services – AIMS 2020
Honolulu, SAD, 2020. str. 30-44 doi:10.1007/978-3-030-59605-7_3 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Kurdija, A., Afrić, P., Šikić, L., Plejić, B., Šilić, M., Delač, G., Vladimir, K. & Srbljić, S. (2020) Candidate Classification and Skill Recommendation in a CV Recommender System. U: Artificial Intelligence and Mobile Services – AIMS 2020 doi:10.1007/978-3-030-59605-7_3.
@article{article, year = {2020}, pages = {30-44}, DOI = {10.1007/978-3-030-59605-7\_3}, keywords = {Recommender systems, Skill recommendation, Spectral clustering, Classification}, doi = {10.1007/978-3-030-59605-7\_3}, title = {Candidate Classification and Skill Recommendation in a CV Recommender System}, keyword = {Recommender systems, Skill recommendation, Spectral clustering, Classification}, publisherplace = {Honolulu, SAD} }
@article{article, year = {2020}, pages = {30-44}, DOI = {10.1007/978-3-030-59605-7\_3}, keywords = {Recommender systems, Skill recommendation, Spectral clustering, Classification}, doi = {10.1007/978-3-030-59605-7\_3}, title = {Candidate Classification and Skill Recommendation in a CV Recommender System}, keyword = {Recommender systems, Skill recommendation, Spectral clustering, Classification}, publisherplace = {Honolulu, SAD} }

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