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  • Search: subject:"Entity extraction"
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Year of publication
Subject
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Entity extraction 2 Machine learning 2 Natural language processing 2 Precision of extraction 2 Text analytics 2 Artificial intelligence 1 Bio data mining 1 Biomedical entity extraction 1 Data Mining 1 Data mining 1 Künstliche Intelligenz 1 Multitask learning 1 Neural network 1 Single-task learning 1 Text 1 Theorie 1 Theory 1
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Online availability
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Free 2 Undetermined 1
Type of publication
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Article 3
Type of publication (narrower categories)
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Article 1 Article in journal 1 Aufsatz in Zeitschrift 1 research-article 1
Language
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English 3
Author
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Trimi, Silvana 2 Zaghloul, Waleed 2 Kumar, Ashutosh 1 Sharaff, Aakanksha 1
Published in...
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Data Technologies and Applications 1 International Journal of Quality Innovation 1 International journal of quality innovation 1
Source
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ECONIS (ZBW) 1 EconStor 1 Other ZBW resources 1
Showing 1 - 3 of 3
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ABEE: automated bio entity extraction from biomedical text documents
Kumar, Ashutosh; Sharaff, Aakanksha - In: Data Technologies and Applications 57 (2023) 2, pp. 222-244
without having any ambiguity from biomedical texts. Design/methodology/approach In the proposed automated bio entity … extraction (ABEE) model, a multitask learning model has been introduced with the combination of single-task learning models. Our …
Persistent link: https://www.econbiz.de/10014712666
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Developing an innovative entity extraction method for unstructured data
Zaghloul, Waleed; Trimi, Silvana - In: International Journal of Quality Innovation 3 (2017) 3, pp. 1-10
The main goal of this study is to build high-precision extractors for entities such as Person and Organization as a good initial seed that can be used for training and learning in machine-learning systems, for the same categories, other categories, and across domains, languages, and...
Persistent link: https://www.econbiz.de/10011808322
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Cover Image
Developing an innovative entity extraction method for unstructured data
Zaghloul, Waleed; Trimi, Silvana - In: International journal of quality innovation 3 (2017) 3, pp. 1-10
The main goal of this study is to build high-precision extractors for entities such as Person and Organization as a good initial seed that can be used for training and learning in machine-learning systems, for the same categories, other categories, and across domains, languages, and...
Persistent link: https://www.econbiz.de/10011747585
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