基于主观性文本的意见挖掘技术是一种在多种领域都有广泛应用的语言技术。该文把评价性语素作为研究对象,在哈尔滨工业大学的语言技术平台(LTP)对语料处理结果的基础上,利用SBV极性传递法为核心,引入指代消解、ATT链算法和互信息法对语料中的评价对象进行抽取,并在对极性词进行倾向性判别时,充分考虑了不同类型的句子,以及副词、连词对极性的影响,尤其是对一般副词、贬义副词和副词“太”作了详细地探讨,最后提出了一个综合的解决方案。该方案结构层次清晰,易于理解,并且其算法复杂度较低。但由于利用的是较为浅层的句法分析结果和基于经验的语言模式方法,该文提出的方案对句法分析结果的依赖度较大。
Abstract
Opinion mining based on the subjective text is a language technology widely used in various fields. This paper studies on the evaluation morpheme, employing SBV polarity transfer algorithm, anaphora resolution, ATT chain algorithm and mutual information algorithm to extract evaluated objects from corpus results of LTP. Different types of sentences are taken into consideration to identify the orientation of sentiment words. The effects of adverb and conjunction, especially the normal adverb, negative adverb and adverb “Tai” are discussed in detail. Finally, an overall solution is presented with low algorithm complexity, clear structure and easy to understand. However, due to the adoption of basic syntactic analysis and experience-based language pattern, the proposed solution is dependent on syntactic analysis results.
Key wordsevaluated object; orientation; SBV polarity transfer algorithm; anaphora resolution
关键词
评价对象 /
倾向性 /
SBV极性传递法 /
指代消解
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Key words
evaluated object /
orientation /
SBV polarity transfer algorithm /
anaphora resolution
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参考文献
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脚注
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基金
国家自然科学基金资助项目(60773087)
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