XU Yan-hua

Nanjing Normal University

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Yunjiao Zhang

Ludong University

Jing Li

Nanjing Normal University

Huaqun Chen

Nanjing Normal University

Yuchen Chen

Southern University of Science and Technology

Chun’e Fan

Nanjing Normal University

Pei Wang

Nanjing University

Feng Chen

Ludong University

Bing-Xue Hu

Nanjing Normal University

Congcong Cui

Northeast Forestry University

Zhiyuan Sun

Sichuan University

Cooperative Institutions

Nanjing Normal University

Ludong University

Nanjing University

Model Animal Research Center

Chinese Academy of Medical Sciences & Peking Union Medical College

China Pharmaceutical University

Yancheng Institute of Technology

Civil Aviation Flight University of China

Guangxi University of Chinese Medicine

Yancheng Third People's Hospital

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Intracellular TMEM16A is necessary for myogenesis of skeletal muscle

iScience (2022)

Wen Yuan Congcong Cui Jing Li XU Yan-hua Chun’e Fan

Calcium in biology

10.1016/j.isci.2022.105446

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Citations (5)

The Function of New Words' Structure Analysis in Automatic Segmentation

Journal of Yantai Vocational College (2007)

XU Yan-hua

The recognition of unknown words is a difficult point in chineseword segmentation processing,Un-known word is an important reason for causing segmentation mistakes in the automatic words segmentation pro-cessing of large-scale Chinese texts.For solving the bottleneck problem in automatic word segmentation,we analyze the structures of new words in unknown words,summarize the types and sequences of words formation of new words and explore their formation rules in order to provide a set of principles for recognizion and marking unknown words.

Text segmentation

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Identification of Complaint Microblogs based on Multimodal and Bi-layer Fusion Framework

Feng Chen Yunjiao Zhang XU Yan-hua

Monitoring and responding to complaints generated by consumers are critical for enterprises and governments. In this paper we propose a multimodal and bi-layer fusion framework to identify microblogs posted on SinaWeibo, the largest social media platform in China. We design an effective and simple method for feature fusion. Based bag-of words model, we represent text and images of a post of microblogs as a unified representation. Using multimodal features, we propose a bi-layer fusion framework. Experiments on two datasets of 5000 microblogs demonstrate our method performs better than text-based methods. The weighted F-measure reaches 0.904, and F-measure of complaint class is 37.07% higher than the baseline.

Microblogging

Complaint

Identification

Representation

Feature (linguistics)

10.1145/3578741.3578794

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Corpus Based Investigation on High Frequent Maximal Overlapping Ambiguity String in Chinese Word Segmentation

Zhongwen xinxi xuebao (2006)

XU Yan-hua

Overlapping ambiguity is still an open issue in Chinese word segmentation.This paper makes a deep investigation on Maximal Overlapping Ambiguity String(MOAS).First,we discuss the disadvantage of using FBMM to detect OAS.Then,by word omni-segmentation,we collect 14906 high frequent MOASs from People's Daily corpus which contains about 400M characters.For these MOASs,1354270 sample sentences are randomly selected and manually labeled.The results show that about 70% of MOASs with true ambiguity have a strong bias towards one segmentation,and consequently,a disambiguation strategy fon dealing with overlapping ambiguities is put forward.

Text segmentation

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Citations (1)