NLPCC2016
Text
NLP
|...
许可协议: Custom

Overview

Word is the fundamental unit in natural language understanding. However, Chinese sentences consists of the continuous Chinese characters without natural delimiters. Therefore, Chinese word segmentation has become the first mission of Chinese natural language processing, which identifies the sequence of words in a sentence and marks the boundaries between words.

Different with the popular used news dataset, we use more informal texts from Sina Weibo. The training and test data consist of micro-blogs from various topics, such as finance, sports, entertainment, and so on.

Data Collection

The data are collected from Sina Weibo. Both the training and test files are UTF-8 encoded. Besides the training data, we also provide the background data, from which the training and test data are drawn. The purpose of providing the background data is to find the more sophisticated features by the unsupervised way.

Citation

@InProceedings{qiu2016overview,
  Title                    = {Overview of the {NLPCC-ICCPOL} 2016 Shared Task: Chinese Word
Segmentation for Micro-blog Texts},
  Author                   = {Xipeng Qiu and Peng Qian and Zhan Shi},
  Booktitle                = {Proceedings of The Fifth
Conference on Natural Language Processing and Chinese Computing \& The Twenty Fourth
International Conference on Computer Processing of Oriental Languages},
  Year                     = {2016}
}

License

Custom

数据概要
数据格式
Text,
数据量
--
文件大小
38.67MB
发布方
NLP Group at Fudan University
Fudan University is a major public research university in Shanghai, China. It is widely considered as one of the most prestigious and selective universities in China.
数据集反馈
| 78 | 数据量 -- | 大小 38.67MB
NLPCC2016
Text
NLP
许可协议: Custom

Overview

Word is the fundamental unit in natural language understanding. However, Chinese sentences consists of the continuous Chinese characters without natural delimiters. Therefore, Chinese word segmentation has become the first mission of Chinese natural language processing, which identifies the sequence of words in a sentence and marks the boundaries between words.

Different with the popular used news dataset, we use more informal texts from Sina Weibo. The training and test data consist of micro-blogs from various topics, such as finance, sports, entertainment, and so on.

Data Collection

The data are collected from Sina Weibo. Both the training and test files are UTF-8 encoded. Besides the training data, we also provide the background data, from which the training and test data are drawn. The purpose of providing the background data is to find the more sophisticated features by the unsupervised way.

Citation

@InProceedings{qiu2016overview,
  Title                    = {Overview of the {NLPCC-ICCPOL} 2016 Shared Task: Chinese Word
Segmentation for Micro-blog Texts},
  Author                   = {Xipeng Qiu and Peng Qian and Zhan Shi},
  Booktitle                = {Proceedings of The Fifth
Conference on Natural Language Processing and Chinese Computing \& The Twenty Fourth
International Conference on Computer Processing of Oriental Languages},
  Year                     = {2016}
}

License

Custom

数据集反馈
0
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