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        <title>Towards Automatic Thesaurus Construction and Enrichment.</title>
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    <name type="personal">
        <namePart type="given">Amir</namePart>
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    <name type="personal">
        <namePart type="given">Beatrice</namePart>
        <namePart type="family">Daille</namePart>
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    <name type="personal">
        <namePart type="given">Lanza</namePart>
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            <title>Proceedings of the 6th International Workshop on Computational Terminology</title>
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            <namePart type="given">Béatrice</namePart>
            <namePart type="family">Daille</namePart>
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            <namePart type="given">Kyo</namePart>
            <namePart type="family">Kageura</namePart>
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    <abstract>Thesaurus construction with minimum human efforts often relies on automatic methods to discover terms and their relations. Hence, the quality of a thesaurus heavily depends on the chosen methodologies for: (i) building its content (terminology extraction task) and (ii) designing its structure (semantic similarity task). The performance of the existing methods on automatic thesaurus construction is still less accurate than the handcrafted ones of which is important to highlight the drawbacks to let new strategies build more accurate thesauri models. In this paper, we will provide a systematic analysis of existing methods for both tasks and discuss their feasibility based on an Italian Cybersecurity corpus. In particular, we will provide a detailed analysis on how the semantic relationships network of a thesaurus can be automatically built, and investigate the ways to enrich the terminological scope of a thesaurus by taking into account the information contained in external domain-oriented semantic sets.</abstract>
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        <date>2020-05</date>
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%0 Conference Proceedings
%T Towards Automatic Thesaurus Construction and Enrichment.
%A Hazem, Amir
%A Daille, Beatrice
%A Claudia, Lanza
%Y Daille, Béatrice
%Y Kageura, Kyo
%Y Terryn, Ayla Rigouts
%S Proceedings of the 6th International Workshop on Computational Terminology
%D 2020
%8 May
%I European Language Resources Association
%C Marseille, France
%@ 979-10-95546-57-3
%G English
%F hazem-etal-2020-towards
%X Thesaurus construction with minimum human efforts often relies on automatic methods to discover terms and their relations. Hence, the quality of a thesaurus heavily depends on the chosen methodologies for: (i) building its content (terminology extraction task) and (ii) designing its structure (semantic similarity task). The performance of the existing methods on automatic thesaurus construction is still less accurate than the handcrafted ones of which is important to highlight the drawbacks to let new strategies build more accurate thesauri models. In this paper, we will provide a systematic analysis of existing methods for both tasks and discuss their feasibility based on an Italian Cybersecurity corpus. In particular, we will provide a detailed analysis on how the semantic relationships network of a thesaurus can be automatically built, and investigate the ways to enrich the terminological scope of a thesaurus by taking into account the information contained in external domain-oriented semantic sets.
%U https://aclanthology.org/2020.computerm-1.9
%P 62-71

Markdown (Informal)

[Towards Automatic Thesaurus Construction and Enrichment.](https://aclanthology.org/2020.computerm-1.9) (Hazem et al., CompuTerm 2020)

• Towards Automatic Thesaurus Construction and Enrichment. (Hazem et al., CompuTerm 2020)

ACL

• Amir Hazem, Beatrice Daille, and Lanza Claudia. 2020. Towards Automatic Thesaurus Construction and Enrichment.. In Proceedings of the 6th International Workshop on Computational Terminology, pages 62–71, Marseille, France. European Language Resources Association.