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https://www.um.edu.mt/library/oar/handle/123456789/120524
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DC Field | Value | Language |
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dc.date.accessioned | 2024-04-08T13:42:59Z | - |
dc.date.available | 2024-04-08T13:42:59Z | - |
dc.date.issued | 2023 | - |
dc.identifier.citation | Ustinova, E. (2023). Automatic detection and attribution of quotes (Master's dissertation). | en_GB |
dc.identifier.uri | https://www.um.edu.mt/library/oar/handle/123456789/120524 | - |
dc.description | M.Sc. (HLST)(Melit.) | en_GB |
dc.description.abstract | Quotations extraction and attribution are important practical tasks for the media, but most of the presented solutions are monolingual. In this work, I present a complex machine learning-based system for extraction and attribution of direct and indirect quotations, which is trained on English and tested on Czech and Russian data. Czech and Russian test datasets were manually annotated as part of this study. This system is compared against a rule-based baseline model. Baseline model demonstrates better precision in extraction of quotation elements, but low recall. The machine learning-based model is better overall in extracting separate elements of quotations and full quotations as well. | en_GB |
dc.language.iso | en | en_GB |
dc.rights | info:eu-repo/semantics/restrictedAccess | en_GB |
dc.subject | Press | en_GB |
dc.subject | Speech acts (Linguistics) | en_GB |
dc.subject | Indirect speech acts (Linguistics) | en_GB |
dc.subject | Data sets | en_GB |
dc.subject | Machine learning | en_GB |
dc.title | Automatic detection and attribution of quotes | en_GB |
dc.type | masterThesis | en_GB |
dc.rights.holder | The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder. | en_GB |
dc.publisher.institution | University of Malta | en_GB |
dc.publisher.department | Faculty of Information and Communication Technology. Department of Artificial Intelligence | en_GB |
dc.description.reviewed | N/A | en_GB |
dc.contributor.creator | Ustinova, Evgeniya (2023) | - |
Appears in Collections: | Dissertations - FacICT - 2023 Dissertations - FacICTAI - 2023 |
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2318ICTCSA531005071432_1.PDF Restricted Access | 1.88 MB | Adobe PDF | View/Open Request a copy |
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