Evaluating Feature Sets and Classifiers for Sentiment Analysis of Financial News

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• 来源
  《IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technologies》|2014年|71-78|共8页
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• 作者

  Njolstad P.C.S.; Hoysaeter L.S.; Wei Wei; Gulla J.A.;

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• 关键词

  Internet; data mining; electronic publishing; emotion recognition; feature extraction; financial data processing; learning (artificial intelligence); pattern classification; support vector machines; text analysis; tree searching; trees (mathematics); J48 classification trees; Norwegian financial Internet news articles; SVM; domain-specific interpretations; domain-specific sentiment lexica; feature categories; feature classifiers; feature set evaluation; financial news; jargon; lingo; machine learning classifiers; machine learning methods; negative sentiment; positive sentiment; random forests; sentiment analysis; sentiment classifiers; support vector machines; Aggregates; Correlation; Feature extraction; Radio frequency; Reliability; Sentiment analysis; Support vector machines; Artificial neural networks; Decision trees; Feature extraction; Machine learning; Supervised learning; Support vector machines; Text analysis; Web mining;

  机译：互联网;数据挖掘;电子出版;情感识别;特征提取;财务数据处理;学习（人工智能）;模式分类;支持向量机;文本分析;树搜索;树（数学）; J48分类树;挪威金融互联网新闻文章;支持向量机;特定领域的解释;特定领域的情感词汇;特征类别;特征分类器;特征集评估;财经新闻;行话;术语;机器学习分类器;机器学习方法;负面情绪;正面情绪;随机森林;情感分析;情感分类器;支持向量机;集合;相关性;特征提取;射频;可靠性;情感分析;支持向量机;人工神经网络;决策树;特征提取;机器学习;监督学习;支持向量机;文本分析;网络挖掘;