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Titlebook: Advanced Data Mining and Applications; 9th International Co Hiroshi Motoda,Zhaohui Wu,Wei Wang Conference proceedings 2013 Springer-Verlag

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Advanced Data Mining and Applications978-3-642-53914-5Series ISSN 0302-9743 Series E-ISSN 1611-3349
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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/a/image/145499.jpg
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,Berufliche Selbstständigkeit im Wandel, statistics-based and model-based approaches. However, the extraction result is not satisfying when these methods are actually used into an application with large useless data due to the complexity of Chinese. Through analyzing the samples hadn’t been extracted correctly, we found some extracting pa
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Einleitung und Problemstellung,on words with similar sentiment have high possibility to co-occur with each other. We show co-occurrence opinion words are helpful for improving sentiment classification accuracy. We employ the co-training framework to conduct semi-supervised sentiment classification. Experimental results show that
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https://doi.org/10.1007/978-3-531-90253-1tresses on content and rarely involves structural features. Even fewer methods are applicable for heterogeneous network, which is prevalent in the real world, such as bibliographic information network. To address this problem, we propose a new measurement of similarity from the perspective of the he
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