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Sentiment analysis approach to adapt a shallow parsing based sentiment lexicon

机译:一种适应浅析基于浅析词典的情绪分析方法

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With the rapid growing of IT development and e-commerce web sites, increasing trends in people to posting online reviews. Sentiment lexicons has offend used to analyzing the large volume of online review data available and gain useful knowledge from it. Most of the sentiment lexicon are aspect base, uses dependence parsing for extracting the word which are not be able to classify the sentimental word so accurately. Try to propose a method which combines sentiment lexicon and shallow parsing. Which determine aspect and domain base sentiment analysis and then assign polarity to a lexicon. Main merits of proposed methods is that it highly accurate and automatically generating structured to avoiding the cost of manually labelling data. The shallow parsing used to analyses sentence and get the constituents words. It will not considering the internal structure of constituent word, nor specifying their value in sentence. Then using polarity of words positive or negative evolution of the product conclude.
机译:随着IT开发和电子商务网站的快速增长,人们越来越多地发布在线评论。情绪词典有冒犯用于分析大量可用的在线评论数据,并从中获得有用的知识。大多数情绪词典是宽方基础,使用依赖解析来提取不能够如此准确地对感伤字分类的单词。尝试提出一种将情绪词典和浅析结合的方法。确定方面和域基本情感分析,然后将极性分配给词典。所提出的方法的主要优点是它高度准确并自动生成结构化,以避免手动标记数据的成本。用于分析句子并获得成分词的浅层解析。它不会考虑组成词的内部结构,也不会在句子中指定它们的价值。然后使用产品的极性或负面演变的极性结论。

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