larder
发表于 2025-3-23 11:34:19
Critique of the “Theory of Rate Processes”ults. Various vector representations for sentence, TFIDF, latent semantic indexing, and neural network word embedding, are conducted and the experimental results show an alternative solution to enhance the current machine translation with a performance improvement about 0.5 BLEU in French-to-English task and 0.7 BLEU in English-to-Chinese task.
变异
发表于 2025-3-23 14:51:13
Critique of the “Theory of Rate Processes”selves, 10 postgraduate students with good command of Chinese and English all agreed or strongly agreed that the general meaning of the translation by Yes Translate was correct and understandable. And 9 out of the 10 students agreed or strongly agreed that the general meaning of each sentence was correct.
抗生素
发表于 2025-3-23 21:13:50
http://reply.papertrans.cn/23/2258/225766/225766_13.png
Lipoprotein(A)
发表于 2025-3-24 01:09:47
János Tóth,Attila László Nagy,Dávid Pappral network model and utilizes this model to identification and classification for Tibetan person attributes, and achieved good results. This research has a very important role in the search engine, information security, machine translation and many other applications.
木讷
发表于 2025-3-24 04:04:36
I Can Guess What You Mean: A Monolingual Query Enhancement for Machine Translationults. Various vector representations for sentence, TFIDF, latent semantic indexing, and neural network word embedding, are conducted and the experimental results show an alternative solution to enhance the current machine translation with a performance improvement about 0.5 BLEU in French-to-English task and 0.7 BLEU in English-to-Chinese task.
Lignans
发表于 2025-3-24 07:21:31
Keeping the Meanings of the Source Text: An Introduction to Yes Translateselves, 10 postgraduate students with good command of Chinese and English all agreed or strongly agreed that the general meaning of the translation by Yes Translate was correct and understandable. And 9 out of the 10 students agreed or strongly agreed that the general meaning of each sentence was correct.
ABOUT
发表于 2025-3-24 10:49:41
Using Collaborative Training Method to Build Vietnamese Dependency Treebankally to do tenfold cross-test and obtained the accuracy of 76.33 %. Experimental results showed that the proposed method in this paper could take full advantage of unmarked corpus to effectively improve the quality of dependency treebank.
参考书目
发表于 2025-3-24 17:18:08
Tibetan Person Attributes Extraction Based on BP Neural Networkral network model and utilizes this model to identification and classification for Tibetan person attributes, and achieved good results. This research has a very important role in the search engine, information security, machine translation and many other applications.
Ascribe
发表于 2025-3-24 23:04:53
0302-9743 CL 2016, and the 4th International Symposium on Natural Language Processing Based on Naturally Annotated Big Data, NLP-NABD 2016, held in Yantai City, China, in October 2016. .The 29 full papers and 8 short papers presented in this volume were carefully reviewed and selected from 85 submissions. The
彻底明白
发表于 2025-3-25 00:49:26
Characteristics of Our Reaction Kineticsinformation. Our model achieves state-of-the-art accuracy on Chinese Penn Treebank and competitive accuracy on English Penn Treebank with only first-order features. Moreover, our model shows effectiveness in recovering dependencies involving out-of-vocabulary words.