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Sentiment analysis and the complex natural language
There is huge amount of content produced online by amateur authors, covering a large
variety of topics. Sentiment analysis (SA) extracts and aggregates users' sentiments towards …
variety of topics. Sentiment analysis (SA) extracts and aggregates users' sentiments towards …
Turning from TF-IDF to TF-IGM for term weighting in text classification
K Chen, Z Zhang, J Long, H Zhang - Expert Systems with Applications, 2016 - Elsevier
Massive textual data management and mining usually rely on automatic text classification
technology. Term weighting is a basic problem in text classification and directly affects the …
technology. Term weighting is a basic problem in text classification and directly affects the …
Inductive learning algorithms and representations for text categorization
Text categorization–the assignment of natural language texts to one or more predefined
categories based on their content–is an important component in many information …
categories based on their content–is an important component in many information …
KSCB: A novel unsupervised method for text sentiment analysis
In recent years, deep learning models (eg Convolutional Neural Networks (CNN) and Long
Short-Term Memories (LSTM)), have been successfully applied to text sentiment analysis …
Short-Term Memories (LSTM)), have been successfully applied to text sentiment analysis …
ForesTexter: An efficient random forest algorithm for imbalanced text categorization
In this paper, we propose a new random forest (RF) based ensemble method, F ores T exter,
to solve the imbalanced text categorization problems. RF has shown great success in many …
to solve the imbalanced text categorization problems. RF has shown great success in many …
[PDF][PDF] A comparative study on different types of approaches to text categorization
Text Categorization is a pattern classification task for text mining and necessary for efficient
management of textual information systems. The documents can be classified by three ways …
management of textual information systems. The documents can be classified by three ways …
[PDF][PDF] 基于机器学**的文本分类技术研究进展
苏金树， 张博锋， 徐昕 [1 - 软件学报, 2006 - Citeseer
文本自动分类是信息检索与数据挖掘领域的研究热点与核心技术, **年来得到了广泛的关注和
快速的发展. 提出了基于机器学**的文本分类技术所面临的互联网内容信息处理等复杂应用的 …
快速的发展. 提出了基于机器学**的文本分类技术所面临的互联网内容信息处理等复杂应用的 …
[PDF][PDF] Representation and classification of text documents: A brief review
Text classification is one of the important research issues in the field of text mining, where
the documents are classified with supervised knowledge. In literature we can find many text …
the documents are classified with supervised knowledge. In literature we can find many text …
SBMDS: an interpretable string based malware detection system using SVM ensemble with bagging
Malicious executables are programs designed to infiltrate or damage a computer system
without the owner's consent, which have become a serious threat to the security of computer …
without the owner's consent, which have become a serious threat to the security of computer …
Random walk term weighting for improved text classification
This paper describes a new approach for estimating term weights in a document, and shows
how the new weighting scheme can be used to improve the accuracy of a text classifier. The …
how the new weighting scheme can be used to improve the accuracy of a text classifier. The …