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Titlebook: Computational Linguistics and Intelligent Text Processing; 15th International C Alexander Gelbukh Conference proceedings 2014 Springer-Verl

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樓主: 傳家寶
21#
發(fā)表于 2025-3-25 03:53:11 | 只看該作者
https://doi.org/10.1007/978-3-319-05567-1nizer. Identification and classification of chemical entities are relatively more complex and challenging compared to the other related tasks. As chemical entities we focus on IUPAC and IUPAC related entities. The algorithm performs feature selection within the framework of a robust machine learning
22#
發(fā)表于 2025-3-25 07:50:14 | 只看該作者
23#
發(fā)表于 2025-3-25 11:57:28 | 只看該作者
Computational Linguistics and Intelligent Text Processing978-3-642-54906-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
24#
發(fā)表于 2025-3-25 18:19:38 | 只看該作者
25#
發(fā)表于 2025-3-25 23:31:05 | 只看該作者
Student Engagement in Neoliberal Times, there is no computational work available for the language. Finite state morphology is one of the successful approaches applied in a wide variety of languages over the year. Therefore we adapted the finite state approach to analyse morphology of the Bishnupriya Manipuri language.
26#
發(fā)表于 2025-3-26 02:53:40 | 只看該作者
27#
發(fā)表于 2025-3-26 05:18:40 | 只看該作者
Morphological Analysis of the Bishnupriya Manipuri Language Using Finite State Transducers, there is no computational work available for the language. Finite state morphology is one of the successful approaches applied in a wide variety of languages over the year. Therefore we adapted the finite state approach to analyse morphology of the Bishnupriya Manipuri language.
28#
發(fā)表于 2025-3-26 10:15:25 | 只看該作者
29#
發(fā)表于 2025-3-26 13:32:01 | 只看該作者
0302-9743 networks; machine translation and multilingualism; information retrieval; text classification and clustering; text summarization; plagiarism detection; style and spelling checking; speech processing; and applications.978-3-642-54905-2978-3-642-54906-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
30#
發(fā)表于 2025-3-26 17:45:42 | 只看該作者
Lisa M. Hagermoser Sanetti,Hao-Jan Luh those developed for English without language-specific feature engineering. This yields interesting results which line up well with those obtained for other languages, demonstrating the cross-linguistic nature of this type of classification. However, we also discover and discuss issues which require
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