Mitigating Data Sparsity in Integrated Data through Text Conceptualization
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3ATBEKHQ3Z" target="_blank" >RIV/00216208:11320/25:TBEKHQ3Z - isvavai.cz</a>
Result on the web
<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200495506&doi=10.1109%2fICDE60146.2024.00269&partnerID=40&md5=f9315382eb0db99e194933a8b9e99c2b" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200495506&doi=10.1109%2fICDE60146.2024.00269&partnerID=40&md5=f9315382eb0db99e194933a8b9e99c2b</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICDE60146.2024.00269" target="_blank" >10.1109/ICDE60146.2024.00269</a>
Alternative languages
Result language
angličtina
Original language name
Mitigating Data Sparsity in Integrated Data through Text Conceptualization
Original language description
We study the data sparsity problem for data generated from an integration system. We approach the problem from a textual information extraction perspective and propose to conceptualize external documents using the concepts in the integrated schema. We present THOR, a novel system that, unlike related approaches, neither relies on complex rules nor models trained with large annotated corpus, but on the integrated data and its schema without the need for human annotations. An extensive evaluation on the text conceptualization task demonstrates the superiority of our approach in terms of F1-score, effort and use of resources over the state-of-the-art language models. © 2024 IEEE.
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
Proc Int Conf Data Eng
ISBN
979-835031715-2
ISSN
1084-4627
e-ISSN
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Number of pages
15
Pages from-to
3490-3504
Publisher name
IEEE Computer Society
Place of publication
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Event location
Utrecht
Event date
Jan 1, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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