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Collocation Polarity Disambiguation Using Web-based Pseudo Contexts

机译:使用基于Web的伪上下文的搭配极性消歧

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This paper focuses on the task of collocation polarity disambiguation. The collocation refers to a binary tuple of a polarity word and a target (such as (long, battery life) or (long, startup)), in which the sentiment orientation of the polarity word ("long") changes along with different targets ("battery life" or "startup"). To disambiguate a collocation's polarity, previous work always turned to investigate the polarities of its surrounding contexts, and then assigned the majority polarity to the collocation. However, these contexts are limited, thus the resulting polarity is insufficient to be reliable. We therefore propose an unsuper-vised three-component framework to expand some pseudo contexts from web, to help disambiguate a collocation's polarity.Without using any additional labeled data, experiments show that our method is effective.
机译:本文着重介绍配置极性消除歧义的任务。并置是指极性字和目标(例如(长,电池寿命)或(长,启动))的二进制元组,其中极性字(“长”)的情感取向随不同的目标而变化(“电池寿命”或“启动”)。为了消除搭配的极性,以前的工作总是转向调查其周围环境的极性,然后将多数极性分配给搭配。但是,这些情况是有限的,因此产生的极性不足以可靠。因此,我们提出了一个无监督的三组件框架来扩展Web上的某些伪上下文,以帮助消除搭配的极性。在不使用任何其他标记数据的情况下,实验表明我们的方法是有效的。

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