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The paper proposed a segmenting algorithm for Chinese based on extracting local context information. It added the context information of the testing text into ...
The paper proposed a segmenting algorithm for Chinese based on extracting local context information. ... Chinese character, we extract the context information.
The paper proposed a segmenting algorithm for Chinese based on extracting local context information. It added the context information of the testing text into ...
The algorithm focuses on the process of online segmentation and new word detection which achieves a good effect in the close or opening test, and outperforms ...
A New Word Detection Method for Chinese Based on Local Context Information. ... The algorithm focuses on the process of online segmentation and new word detection ...
The extraction of key phrase process is statistical analysis, part-of-speech tagging, named entity recognition, rule-based extraction, and machine learning ...
We propose in this paper the use of graph attention networks to construct relatives among matching words and neighboring characters.
Abstract. Chinese word segmentation is a difficult, im- portant and widely-studied sequence modeling problem. This paper demonstrates the abil-.
Nov 21, 2022 · We use imConvNet model to extract additional word vector features and improve named entity recognition accuracy.
Abstract. There is no blank to mark word boundaries in. Chinese text. As a result, identifying words is difficult, because of segmentation ambiguities.