Domain Adaptation for Resume Classification Using Convolutional Neural Networks
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A4 Artikkeli konferenssijulkaisussa
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en
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12
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Analysis of Images, Social Networks and Texts: 6th International Conference, AIST 2017, Moscow, Russia, July 27--29, 2017, Revised Selected Papers, pp. 82-93, Lecture Notes in Computer Science ; Volume 10716
Abstract
We propose a novel method for classifying resume data of job applicants into 27 different job categories using convolutional neural networks. Since resume data is costly and hard to obtain due to its sensitive nature, we use domain adaptation. In particular, we train a classifier on a large number of freely available job description snippets and then use it to classify resume data. We empirically verify a reasonable classification performance of our approach despite having only a small amount of labeled resume data available.Description
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Sayfullina, L, Malmi, E, Liao, Y & Jung, A 2018, Domain Adaptation for Resume Classification Using Convolutional Neural Networks. in W M P van der Aalst, D I Ignatov, M Khachay, S O Kuznetsov, V Lempitsky, I A Lomazova, N Loukachevitch, A Napoli, A Panchenko, P M Pardalos, A V Savchenko & S Wasserman (eds), Analysis of Images, Social Networks and Texts: 6th International Conference, AIST 2017, Moscow, Russia, July 27--29, 2017, Revised Selected Papers. Lecture Notes in Computer Science, vol. 10716, Springer, Cham, pp. 82-93, International Conference on Analysis of Images, Social Networks and Texts, Moscow, Russian Federation, 27/07/2017. https://doi.org/10.1007/978-3-319-73013-4_8