Topic Classification and Headline Generation for Maltese using a Public News Corpus
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A54ND96K8" target="_blank" >RIV/00216208:11320/25:54ND96K8 - isvavai.cz</a>
Result on the web
<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195961870&partnerID=40&md5=d1f0444efc190f14d9a563f256c8b5ea" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195961870&partnerID=40&md5=d1f0444efc190f14d9a563f256c8b5ea</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Topic Classification and Headline Generation for Maltese using a Public News Corpus
Original language description
The development of NLP tools for low-resource languages is impeded by the lack of data. While recent unsupervised pre-training approaches ease this requirement, the need for labelled data is crucial to progress the development of such tools. Moreover, publicly available datasets for such languages typically cover low-level syntactic tasks. In this work, we introduce new semantic datasets for Maltese generated automatically using associated metadata from a corpus in the news domain. The datasets are a news tag multi-label classification and a news abstractive summarisation task by generating its title. We also present an evaluation using publicly available models as baselines. Our results show that current models are lacking the semantic knowledge required to solve such tasks, shedding light on the need to use better modelling approaches for Maltese. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Jt. Int. Conf. Comput. Linguist., Lang. Resour. Eval., LREC-COLING - Main Conf. Proc.
ISBN
978-249381410-4
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
16274-16281
Publisher name
European Language Resources Association (ELRA)
Place of publication
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Event location
Torino, Italia
Event date
Jan 1, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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