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情感分析的目标范围从积极到消极。与其他NLP工作一样，它通常被认为是一个分类问题，尽管当精度很重要时，它可以被视为一个回归问题。 情感分析过去是由大量劳动力阅读和手动评估文本来完成的。这种方法成本高昂，而且容易出现人为错误。为了使这一过程自动化，公司寻求先进的分析方法来解决这一问题。 情感分析的挑战在于人们表达和解释情绪的极性和强度不同。此外，单词和句子可以根据上下文有多种含义（称为多义）。虽然其中一些问题可以缓解，但与任何分析任务一样，速度和性能之间几乎总是存在权衡。
natural language processing emotion analysis
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2023-06-15 14:29:41
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