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Chinese text sentiment classification based on granule network
2009 IEEE International Conference on Granular Computing, 2009With the expanding of text comment information, text sentiment classification become a hot issue. Domestic research on chinese sentiment classification mainly focus on segmentation and features selection or focus on classifying algorithm based on statistics. Rules mining method is a kind of important techniques of text classification.
Xia Zhang +3 more
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Performance of using LDA for Chinese news text classification
2015 IEEE 28th Canadian Conference on Electrical and Computer Engineering (CCECE), 2015Chinese text classification is always challenging, especially when data are high dimensional and sparse. In this paper, we are interested in the way of text representation and dimension reduction in Chinese text classification. First, we introduces a topic model — Latent Dirichlet Allocation(LDA), which is uses LDA model as a dimension reduction method.
Xiaojun Wu, Liying Fang, Pu Wang, Nan Yu
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A Chinese Text Classification Approach Based on Semantic Web
2008 Fourth International Conference on Semantics, Knowledge and Grid, 2008This paper discusses a approach of Chinese text classification on semantic Web. It is given one classified technology based on the semantic concept established on the "How-net" . It extracts keywords from text, analyses the full text using the keywords concept, and then the integrates to classify by categories of keywords semantic concept.
Shiqun Yin +3 more
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Accurate Chinese Text Classification via Multiple Strategies
Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007), 2007Text classification is one of means to understand text content. It is widely used in information retrieving, filtering spam, monitoring ill gossips, and blocking pornographic and evil messages. kN N is widely used in text categorization, but it suffers from biased training data set.
Xiulan Hao +4 more
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The Research of Semantic Kernel in SVM for Chinese Text Classification
Proceedings of the 2nd International Conference on Intelligent Information Processing, 2017The study of semantic kernel function is an important branch of kernel function research in recent years. However, there are few studies on the use of semantic kernel function in support vector machine for Chinese text classification. This paper constructs a domain-related weight matrix based on statistical features and a semantic kernel function based
Fanjin Mai +3 more
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Semantic and Morphological Information Guided Chinese Text Classification
2019Recently proposed models such as BERT, perform well in many text processing tasks. They get context-sensitive features, which is a good semantic for word sense disambiguation, through deeper layer and a large number of texts. But, for Chinese text classification, majority of datasets are crawled from social networking sites, these datasets are ...
Jiayu Song +4 more
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Chinese Text Classification via Bidirectional Lattice LSTM
2020In this paper, we investigate a bidirectional lattice LSTM (Bi-Lattice) network for Chinese text classification. The new network is different from the standard LSTM in adding shortcut paths which link the start and end characters of words, to control the information flow.
Ning Pang +2 more
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Automatic Chinese Text Classification Based on NSVMDT-KNN
2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery, 2008According to this paper, a novel approach based on non-linear support vetor machine decision tree (NSVMDT) and K nearest neighbors (KNN) is proposed towards Chinese text categorization. To begin with, SVM is extended to non-linear SVM by using kernel functions.
QiNan Xu, Zhijng Liu
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Chinese Text Classification without Automatic Word Segmentation
Sixth International Conference on Advanced Language Processing and Web Information Technology (ALPIT 2007), 2007Due to the lack of word boundaries in Asian systems of writing, machine processing of these languages often involves segmenting text into word units. This paper tests the assumption that this segmentation is a necessary step for authorship attribution and topic classification tasks in Chinese, and demonstrates that it is not.
Wei Liu 0034 +3 more
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