| Publication type: | Conference paper |
| Type of review: | Peer review (publication) |
| Title: | Skill extraction for domain-specific text retrieval in a job-matching platform |
| Authors: | Smith, Ellery Weiler, Andreas Braschler, Martin |
| et. al: | No |
| DOI: | 10.1007/978-3-030-85251-1_10 |
| Proceedings: | Experimental IR Meets Multilinguality, Multimodality, and Interaction |
| Editors of the parent work: | Candan, K. Selçuk Ionescu, Bogdan Goeuriot, Lorraine Larsen, Birger Müller, Henning Joly, Alexis Maistro, Maria Piroi, Florina Faggioli, Gugliemlo Ferro, Nicola |
| Page(s): | 116 |
| Pages to: | 128 |
| Conference details: | 12th International Conference of the CLEF Association (CLEF 2021), virtual event, 21–24 September 2021 |
| Issue Date: | 2021 |
| Series: | Lecture Notes in Computer Science |
| Series volume: | 12880 |
| Publisher / Ed. Institution: | Springer |
| Publisher / Ed. Institution: | Cham |
| ISBN: | 978-3-030-85250-4 978-3-030-85251-1 |
| ISSN: | 0302-9743 1611-3349 |
| Language: | English |
| Subjects: | Information retrieval; Domain-specific retrieval; Term extraction; Natural language processing |
| Subject (DDC): | 006: Special computer methods |
| Abstract: | We discuss a domain-specific retrieval application for matching job seekers with open positions that uses a novel syntactic method of extracting skill-terms from the text of natural language job advertisements. Our new method is contrasted with two word embeddings methods, using word2vec. We define the notion of a skill headword, and present an algorithm that learns syntactic dependency patterns to recognize skill-terms. In all metrics, our syntactic method outperforms both word embeddings methods. Moreover, the word embeddings approaches were unable to model a meaningful distinction between skill-terms and non-skill-terms, while our syntactic approach was able to perform this successfully. We also show how these extracted skills can be used to automatically construct a semantic job-skills ontology, and facilitate a job-to-candidate matching system. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/24567 |
| Fulltext version: | Published version |
| License (according to publishing contract): | Licence according to publishing contract |
| Departement: | School of Engineering |
| Organisational Unit: | Institute of Applied Information Technology (InIT) |
| Published as part of the ZHAW project: | Skillue - Digitaler Marktplatz für Fähigkeiten und Marktwerte |
| Appears in collections: | Publikationen School of Engineering |
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