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Titlebook: Natural Language Processing and Chinese Computing; 11th CCF Internation Wei Lu,Shujian Huang,Xiabing Zhou Conference proceedings 2022 The E

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樓主: Harrison
41#
發(fā)表于 2025-3-28 18:11:38 | 只看該作者
42#
發(fā)表于 2025-3-28 19:02:21 | 只看該作者
43#
發(fā)表于 2025-3-29 00:17:53 | 只看該作者
Exploiting Dynamic and?Fine-grained Semantic Scope for?Extreme Multi-label Text Classificationl set. A majority of labels only have a few training instances due to large label dimensionality in XMTC. To solve this data sparsity issue, most existing XMTC methods take advantage of fixed label clusters obtained in early stage to balance performance on tail labels and head labels. However, such
44#
發(fā)表于 2025-3-29 05:44:15 | 只看該作者
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發(fā)表于 2025-3-29 07:36:24 | 只看該作者
Semi-supervised Protein-Protein Interactions Extraction Method Based on Label Propagation and Sententhe field of biomedicine. Extracting PPI information from the literature can provide meaningful references for related research. In order to build an automated PPI extraction system, labeled corpora are required. However, labeled corpora are very limited, and annotating corpora is a time-consuming,
46#
發(fā)表于 2025-3-29 14:25:10 | 只看該作者
Construction and Application of a Large-Scale Chinese Abstractness Lexicon Based on Word Similarity have constructed their abstractness lexicons, while there has never been a large-scale and high-quality abstractness lexicon in Chinese. Since manual construction is time-consuming and costly, we use the existing resources with human abstractness scores as original data, and adopt the word similari
47#
發(fā)表于 2025-3-29 19:21:21 | 只看該作者
48#
發(fā)表于 2025-3-29 20:19:00 | 只看該作者
Context Enhanced and?Data Augmented , System for?Named Entity Recognition Literature. This task needs participants to develop a named entity recognition (NER) model for domain-specific texts based on state-of-the-art NLP and deep learning techniques with the labeled domain-specific sentences corresponding to seven entity types. Without the luxury of training data, we pro
49#
發(fā)表于 2025-3-30 00:28:10 | 只看該作者
50#
發(fā)表于 2025-3-30 04:03:55 | 只看該作者
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