Add to ORKGThis paper describes our participation in the Chinese word segmentation task of CIPS-SIGHAN 2010. We implemented an n-gram mutual information (NGMI) based segmentation algorithm with the mixed-up features from unsupervised, supervised and dictionarybased segmentation methods. This algorithm is also combined with a simple strategy for out-of-vocabulary (OOV) word recognition. The evaluation for both open and closed training shows encouraging results of our system. The results for OOV word recognition in closed training evaluation were however found unsatisfactory
Abstract- Proposed an approach of Chinese word segmenta-tion based on statistic and rules. The appro...
This paper summarizes the SIGHAN 2014 Chinese Word Segmentation bake-off in several aspects such as ...
In this paper, we propose a joint model for unsupervised Chinese word segmentation (CWS). Inspired b...
This paper describes our participation in the Chinese word segmentation task of CIPS-SIGHAN 2010. We...
This paper describes our participation\ud in the Chinese word segmentation task\ud of CIPS-SIGHAN 20...
In this paper, we propose an unsupervised segmentation approach, named "n-gram mutual information", ...
The fact that words are not conventionally demarcated in Chinese orthography makes the process of wo...
Abstract In this paper, we propose an unsupervised seg-mentation approach, named "n-gram mutual...
A Chinese sentence is typically written as a sequence of characters. However, a word, a logical sema...
Word segmentation is the first step in Chinese information processing, and the performance of the se...
This paper addresses two remaining challenges in Chinese word segmentation. The challenge in HLT is ...
This thesis proposes an approach to generating n-gram features for Conditional Random Fields (CRFs) ...
As the amount of online Chinese contents grows, there is a critical need for effective Chinese word ...
In order to analyze security and terrorism related content in Chinese, it is important to perform wo...
This paper presents a bilingual semi-supervised Chinese word segmentation (CWS) method that leverage...
Abstract- Proposed an approach of Chinese word segmenta-tion based on statistic and rules. The appro...
This paper summarizes the SIGHAN 2014 Chinese Word Segmentation bake-off in several aspects such as ...
In this paper, we propose a joint model for unsupervised Chinese word segmentation (CWS). Inspired b...
This paper describes our participation in the Chinese word segmentation task of CIPS-SIGHAN 2010. We...
This paper describes our participation\ud in the Chinese word segmentation task\ud of CIPS-SIGHAN 20...
In this paper, we propose an unsupervised segmentation approach, named "n-gram mutual information", ...
The fact that words are not conventionally demarcated in Chinese orthography makes the process of wo...
Abstract In this paper, we propose an unsupervised seg-mentation approach, named "n-gram mutual...
A Chinese sentence is typically written as a sequence of characters. However, a word, a logical sema...
Word segmentation is the first step in Chinese information processing, and the performance of the se...
This paper addresses two remaining challenges in Chinese word segmentation. The challenge in HLT is ...
This thesis proposes an approach to generating n-gram features for Conditional Random Fields (CRFs) ...
As the amount of online Chinese contents grows, there is a critical need for effective Chinese word ...
In order to analyze security and terrorism related content in Chinese, it is important to perform wo...
This paper presents a bilingual semi-supervised Chinese word segmentation (CWS) method that leverage...
Abstract- Proposed an approach of Chinese word segmenta-tion based on statistic and rules. The appro...
This paper summarizes the SIGHAN 2014 Chinese Word Segmentation bake-off in several aspects such as ...
In this paper, we propose a joint model for unsupervised Chinese word segmentation (CWS). Inspired b...