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介绍了基于Windows 2000 的切割机数控系统,该系统充分运用了开放式数控系统多层次、模块化和开放式的设计方法。针对切割机这一特殊的数控系统,分析了割缝补偿、速度预处理、PLC等几个重要功能模块的实现方法。 相似文献
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Sentiment analysis is the computational study of how opinions, attitudes, emotions, and perspectives are expressed in language, and has been the important task of natural language processing. Sentiment analysis is highly valuable for both research and practical applications. The focuses were put on the difficulties in the construction of sentiment classifiers which normally need tremendous labeled domain training data, and a novel unsupervised framework was proposed to make use of the Chinese idiom resources to develop a general sentiment classifier. Furthermore, the domain adaption of general sentiment classifier was improved by taking the general classifier as the base of a self-training procedure to get a domain self-training sentiment classifier. To validate the effect of the unsupervised framework, several experiments were carried out on publicly available Chinese online reviews dataset. The experiments show that the proposed framework is effective and achieves encouraging results. Specifically, the general classifier outperforms two baselines(a Na?ve 50% baseline and a cross-domain classifier), and the bootstrapping self-training classifier approximates the upper bound domain-specific classifier with the lowest accuracy of 81.5%, but the performance is more stable and the framework needs no labeled training dataset. 相似文献
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随着社交媒体的迅速发展,信息过载问题越发严重,因此如何从海量、短小而充满噪声的社交媒体数据中发现和挖掘出热点话题或者热点事件成为一个重要的问题。结合社交媒体数据实时性、地理性、包含较多元数据等特点,提出了用户行为分析与文本内容分析相结合的热点挖掘方法。在内容分析过程中,提出了从更细的词语粒度进行聚类,以代替传统的在消息粒度进行聚类的经典方法。为了提高话题关键词提取的效果,引入了基于词向量技术,并通过语义聚类的方法进行热点挖掘。在真实数据集上的实验结果表明,该方法提取的关键词语义关联性强、话题划分效果好,在主要指标上优于传统的热点挖掘方法。 相似文献
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覆盖面广且领域适应性好的情感词典可以有效提高文本情感分析效能。设计了基于连词语言特征和词性特征向量统计特征的中文情感词典扩展算法,提出了综合两种方法的混合特征算法。算法计算得到词语的细粒度的积极和消极情感极性值,并对通用情感词典在领域内进行扩展以提高覆盖度,对词典进行领域内调整以提高适应性。实验结果表明,算法在领域内扩展获得的词典比通用情感词典覆盖度和适应性更好,在情感分类任务中性能接近有监督方法。 相似文献
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