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

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POLYP

Tibetan Person Attributes Extraction Based on BP Neural Networkn on the network. In the face of the massive network information, extracting the information that people want is an urgent problem to be solved. Currently, Chinese person attributes extraction studies have some good results, but there is still much space to Tibetan person attributes extraction. The

個阿姨勾引你

Semi-supervised Learning for Mongolian Morphological Segmentationore a novel semi-supervised method for a practical application, i.e., statistical machine translation (SMT), based on a low-resource learning setting, in which a small amount of labeled data and large amount of unlabeled data are available. First, a CRF-based supervised learning is exploited to pred

nocturnal

reperfusion

Recognizing Biomedical Named Entities Based on the Sentence Vector/Twin Word Embeddings Conditioned network has been applied on the entity recognition to avoid the complex hand-designed features, which are derived from various linguistic analyses. However, performance of the conventional neural network systems is always limited to exploiting long range dependencies in sentences. In this paper, we

會犯錯誤

https://doi.org/10.1007/978-981-19-9673-3tion errors decrease significantly after English sentences are parsed into NT clauses. This result reveals that non-SV clauses are the main source of MT errors, and suggests that English long sentences should be parsed into NT clauses before they are translated.

損壞

Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big D15th China National

哪有黃油

Error Analysis of English-Chinese Machine Translationtion errors decrease significantly after English sentences are parsed into NT clauses. This result reveals that non-SV clauses are the main source of MT errors, and suggests that English long sentences should be parsed into NT clauses before they are translated.

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Triglyceride

978-3-319-47673-5Springer International Publishing AG 2016