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SUBJECTIVITY WORD SENSE DISAMBIGUATION: A METHOD FOR SENSE-AWARE SUBJECTIVITY ANALYSIS

机译:主体性词义消歧:感知感知主体性分析的一种方法

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摘要

Subjectivity lexicons have been invaluable resources in subjectivity analysis and their creation has been an important topic. Many systems rely on these lexicons. For any subjectivity analysis system, which relies on a subjectivity lexicon, subjectivity sense ambiguity is a serious problem. Such systems will be misled by the presence of subjectivity clues used with objective senses called false hits.udWe believe that any type of subjectivity analysis system relying on lexicons will benefit from a sense-aware approach. We think sense-aware subjectivity analysis has been neglected mostly because of the concerns related to word sense disambiguation (WSD), the problem of automatically determining which sense of a word is activated by the use of the word in a particular context according to a sense-inventory. Although WSD is the perfect tool for sense-aware classification, trust in traditional fine-grained WSD as an enabling technology is not high due to previous mostly unsuccessful results.udIn this thesis, we investigate feasible and practical methods to avoid these false hits via sense-aware analysis. We define a new coarse-grained WSD task capturing the right semantic granularity specific to subjectivity analysis.
机译:主体性词典是主体性分析中的宝贵资源,其创建已成为一个重要的主题。许多系统都依赖这些词典。对于任何依赖于主观性词典的主观性分析系统,主观性的含糊性都是一个严重的问题。这种系统将被存在于客观感知中的被称为虚假命中的主观线索所误导。 ud我们相信,依赖于词典的任何类型的主观分析系统都将受益于感知感知方法。我们认为意识感知的主观分析主要是由于与词义歧义消除(WSD)有关的问题而被忽略,WSD是通过根据特定意义在特定上下文中使用该词来自动确定一个词义被激活的问题-库存。尽管WSD是感知感知分类的理想工具,但由于以前大多不成功,因此对传统的细粒度WSD作为支持技术的信任度并不高。 ud在本文中,我们研究了可行和实用的方法来避免这些错误的点击感知分析。我们定义了一个新的粗粒度WSD任务,该任务捕获了特定于主观分析的正确语义粒度。

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    AKKAYA CEM;

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  • 年度 2014
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