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- W2808001702 abstract "As librarianship evolves, it is important to understand the changes taken place in its core competencies. One good way to do this is to analyze job advertisements (ads) for professional librarian positions. Most related works are based on manual method; the semi-automatic framework requires a classifier consisting of manual rulesets as input. In this paper, a framework and a multi-label short text clustering algorithm, ICNTC, are proposed to automatically identify core competencies from job ads. Data from the American Library Association (ALA) Joblist from 2009 through 2014 is used to validate the method. The analysis of experiment results shows that the method may identify most of core competencies, with a good performance in evaluating the frequency of each competencies. The accuracy of keyword extraction on ALA dataset is 89 ± 1.3%." @default.
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- W2808001702 date "2018-01-01" @default.
- W2808001702 modified "2023-10-06" @default.
- W2808001702 title "Core Competencies Keywords Discovering Algorithm for Employment Advertisements" @default.
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- W2808001702 doi "https://doi.org/10.1007/978-981-13-0896-3_22" @default.
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