Results 251 to 260 of about 44,658,676 (284)

Orthographic features for emotion classification in Chinese in informal short texts

Language Resources and Evaluation, 2020
Informal short texts on the web are rich in emotions as they often reflect unfiltered immediate reactions to breaking news events. The emotion density, however, stands in contrast to its poverty of linguistic contexts and features for emotion classification.
Chen, I-Hsuan, Long, Yunfei, Lu, Qin, Huang, Chu-Ren   +3 more
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Hybrid Attention Networks for Chinese Short Text Classification

Computación y Sistemas, 2018
To improve the classification performance for Chinese short text with automatic semantic feature selection, in this paper we propose the Hybrid Attention Networks (HANs) which combines the word- and character-level selective attentions. The model firstly applies RNN and CNN to extract the semantic features of texts.
Yujun Zhou 0001, Jiaming Xu 0001, Jie Cao, Bo Xu 0011, Changliang Li, Bo Xu 0002   +5 more
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Chinese Short Text Classification with Mutual-Attention Convolutional Neural Networks

ACM Transactions on Asian and Low-Resource Language Information Processing, 2020
The methods based on the combination of word-level and character-level features can effectively boost performance on Chinese short text classification. A lot of works concatenate two-level features with little processing, which leads to losing feature information.
Ming Hao, Bo Xu 0002, Jing-Yi Liang, Bo-Wen Zhang 0011, Xu-Cheng Yin   +4 more
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Hot Topic Detection on Chinese Short Text

2011
Concerning the short length, weak ability to describe the characteristics of short text, an approach of hot topic detection of Chinese short text was put forward by using hyponymy extending the key-feature vectors. First, cluster Chinese short texts and extract keywords, then, use “HowNet” hyponymy to extend the keywords, finally, cluster the extended ...
Cheng Zhang, Xinghua Fan, Xianlin Chen
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Sentiment analysis for short Chinese text based on character-level methods

2017 9th International Conference on Knowledge and Smart Technology (KST), 2017
To date, analyzing the sentiment of user-generated reviews is an important way to get timely feedbacks from customers. In order to solve the task, many semantics methods and machine learning algorithms are applied. However, most of them are based on word-level features.
Yanxin An, Xinhuai Tang, Bin Xie
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Joint SPSL and CCWR for Chinese Short Text Entity Recognition and Linking

2020
Entity Recognition Linking (ERL) is a basic task of Natural Language Processing (NLP), which is an extension of the Named Entity Recognition (NER) task. The purpose of the ERL is to detect the entity from a given Chinese short text, and the detected entity is linking to the corresponding entity in the given knowledge library.
Zhiqiang Chong, Zhiming Liu 0003, Zhi Tang 0007, Lingyun Luo, Yaping Wan   +4 more
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Linking Entities in Short Texts Based on a Chinese Semantic Knowledge Base

2013
Populating existing knowledge base with new facts is important to keep the knowledge base fresh and most updated. Before importing new knowledge into the knowledge base, entity linking is required so that the entities in the new knowledge can be linked to the entities in the knowledge base.
Yi Zeng 0001, Dongsheng Wang 0005, Tielin Zhang, Hao Wang, Hongwei Hao   +4 more
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An approach to sentiment analysis of short Chinese texts based on SVMs

2015 34th Chinese Control Conference (CCC), 2015
This paper uses a machine-learning method to determine the sentiment polarity of short Chinese texts. Firstly, a new way to extend the sentiment dictionary is presented. The sentiment dictionaries from NTU and HowNet are extended by using the word2vec tool provided by Google. The review texts are collected from Internet as datasets.
Lu Xing, Li Yuan, Wang Qinglin, Liu Yu
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Chinese Short Text Entity Linking Model Based on PET

Proceedings of the 4th World Symposium on Software Engineering, 2022
Xiaofan Yan, Jie Cheng, Ru Zhang 0002, Jiahui Wei, Liandong Chen, Kai Cheng   +5 more
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Similarity Measures for Chinese Short Text Based on Representation Learning

Journal of Information and Computational Science, 2015
Similarity measure in Chinese short text is an important prerequisite for many content-based texts or documents retrieval tasks. In this paper, we propose a fast method for representing Chinese short texts to calculate the similarity between texts. The method is based on the representation of Chinese words. First, Chinese word representation is learned
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