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Titlebook: Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big D; 15th China National Maosong Sun,Xuan

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樓主: 大破壞
31#
發(fā)表于 2025-3-26 23:41:57 | 只看該作者
Improving Chinese Semantic Role Labeling with English Proposition Bankass approach to do Chinese SRL with a Recurrent Neural Network (RNN) model. We use English Proposition Bank (EPB) to improve the performance of Chinese SRL. Experimental result shows a significant improvement over the state-of-the-art methods on Chinese Proposition Bank (CPB), which reaches 78.39?%
32#
發(fā)表于 2025-3-27 02:36:59 | 只看該作者
33#
發(fā)表于 2025-3-27 07:28:45 | 只看該作者
Improved Graph-Based Dependency Parsing via Hierarchical LSTM Networks learn word representations, allowing our model to avoid the problem of limited-vocabulary and capture both distributional and compositional semantic information. Our model achieves state-of-the-art accuracy on Chinese Penn Treebank and competitive accuracy on English Penn Treebank with only first-o
34#
發(fā)表于 2025-3-27 12:17:32 | 只看該作者
35#
發(fā)表于 2025-3-27 16:05:43 | 只看該作者
36#
發(fā)表于 2025-3-27 20:51:25 | 只看該作者
Keeping the Meanings of the Source Text: An Introduction to Yes Translate get lost or distorted in machine translation, including state-of-the-art Google Translate and Baidu Translate. Yes Translate is a Chinese-English translation tool to be maximally loyal to the source text while maintaining adequate fluency. This is implementable by avoiding risky actions of word del
37#
發(fā)表于 2025-3-28 00:20:30 | 只看該作者
38#
發(fā)表于 2025-3-28 04:00:22 | 只看該作者
39#
發(fā)表于 2025-3-28 06:39:40 | 只看該作者
40#
發(fā)表于 2025-3-28 11:14:03 | 只看該作者
Improved Joint Kazakh POS Tagging and Chunkingmodel. A improved beam-search algorithm use dynamic beam instead of unified beam to obtain search space of small-but-excellent during both training and decoding phases of the model. Moreover we can statistical induction the information of chunk to disambiguation of multi-category words and experimen
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