An Extension of the Aspect PLSA Model to Active and Semi-Supervised Learning for Text Classification

机译：将Aspect PLSA模型扩展到用于文本分类的主动和半监督学习

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In this paper, we address the problem of learning aspect models with partially labeled examples. We propose a method which benefits from both semi-supervised and active learning frameworks. In particular, we combine a semi-supervised extension of the PLSA algorithm [11] with two active learning techniques. We perform experiments over four different datasets and show the effectiveness of the combination of the two frameworks.

机译：在本文中，我们通过部分标记的示例解决了学习方面模型的问题。我们提出一种受益于半监督和主动学习框架的方法。特别是，我们将PLSA算法的半监督扩展[11]与两种主动学习技术结合在一起。我们对四个不同的数据集进行了实验，并展示了这两个框架相结合的有效性。

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来源
《Artificial intelligence: Theories, models and applications》|2010年|p.183-192|共10页
会议地点 Athens(GR);Athens(GR)
作者
Anastasia Krithara; Massih-Reza Amini; Cyril Goutte; Jean-Michel Renders;
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作者单位

National Center for Scientific Research (NCSR) 'Demokritos', Athens, Greece;

National Research Council Canada, Gatineau, Canada;

National Research Council Canada, Gatineau, Canada;

Xerox Research Centre Europe, Grenoble, France;

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原文格式 PDF
正文语种 eng
中图分类人工智能理论;
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机译：使用增强型KNN算法的文本分类中的有监督和半监督学习：文本分类中有监督和半监督分类的比较研究
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4. An Extension of the Aspect PLSA Model to Active and Semi-Supervised Learning for Text Classification [C] . Anastasia Krithara, Massih-Reza Amini, Cyril Goutte, Hellenic Conference on Artificial Intelligence . 2010

机译：方面PLSA模型的延伸，为文本分类的主动和半监督学习
5. Semi-Supervised Machine Learning & Deep Learning Models in Crisis-Related Informativeness Classification [D] . Rennola, Alessandro. 2019

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7. An extension of the aspect PLSA model to active and semi-supervised learning for text classification [O] . Krithara, Anastasia, Amini, Massih-Reza, Goutte, Cyril, 2010

机译：将方面PLSA模型扩展到用于文本分类的主动和半监督学习

An Extension of the Aspect PLSA Model to Active and Semi-Supervised Learning for Text Classification

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