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Ranking job offers for candidates: learning hidden knowledge from Big Data

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dc.contributor.author Poch, Marc
dc.contributor.author Bel Rafecas, Núria
dc.contributor.author Espeja, Sergio
dc.contributor.author Navío, Felipe
dc.date.accessioned 2019-03-08T11:15:04Z
dc.date.available 2019-03-08T11:15:04Z
dc.date.issued 2014
dc.identifier.citation Poch M, Bel N, Espeja S, Navío F. Ranking job offers for candidates: learning hidden knowledge from Big Data. In: Calzolari N, Choukri K, Declerck T, Loftsson H, Maegaard B, Mariani J, Moreno A, Odijk J, Piperidis S, editors. Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC-2014); 2014 May 26-31; Reykjavik, Iceland. Paris: European Language Resources Association; 2014. p. 2076-82.
dc.identifier.uri http://hdl.handle.net/10230/36781
dc.description Comunicació presentada a: 9th International Conference on Language Resources and Evaluation celebrada del 26 al 31 de maig de 2014 a Reykjavik, Iceland.
dc.description.abstract This paper presents a system for suggesting a ranked list of appropriate vacancy descriptions to job seekers in a job board web site. In particular our work has explored the use of supervised classifiers with the objective of learning implicit relations which cannot be found with similarity or pattern based search methods that rely only on explicit information. Skills, names of professions and degrees, among other examples, are expressed in different languages, showing high variation and the use of ad-hoc resources to trace the relations is very costly. This implicit information is unveiled when a candidate applies for a job and therefore it is information that can be used for learning a model to predict new cases. The results of our experiments, which combine different clustering, classification and ranking methods, show the validity of the approach.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher ACL (Association for Computational Linguistics)
dc.relation.ispartof In: Calzolari N, Choukri K, Declerck T, Loftsson H, Maegaard B, Mariani J, Moreno A, Odijk J, Piperidis S, editors. Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC-2014); 2014 May 26-31; Reykjavik, Iceland. Paris: European Language Resources Association; 2014. p. 2076-82.
dc.rights © ACL, Creative Commons Attribution 3.0 License
dc.rights.uri https://creativecommons.org/licenses/by/3.0/es/
dc.title Ranking job offers for candidates: learning hidden knowledge from Big Data
dc.type info:eu-repo/semantics/conferenceObject
dc.subject.keyword Multilingual data
dc.subject.keyword E-recruiting
dc.subject.keyword LDA clustering methods
dc.subject.keyword Ranking methods
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion

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