Domain adaptation in sentiment analysis is one of the areas where a classifier trained in one domain often classifies sentiments poorly when applied to another domain due to domain-specific words. Extracting features and their relevant opinion words from different domain sources and mapping them to the target domains are herculean tasks as far as domain adaptation is concerned. In this paper, the feature extraction technique is refined by which the mapping task is enhanced. The feature extraction technique uses both the syntactic and semantic properties of the features for extracting similar words. The features are further refined by merging synonyms and by replacing negative polarity terms with the appropriate antonyms. This refinement in the feature selection improves the mapping functionality of the domain adaptation and also exploits the relationship between domain-specific words and domain-independent words from different domains.

情感分析中的领域适应是其中一个领域中训练的分类器由于应用于领域的特定单词而在应用于另一个领域时常常无法很好地对情感进行分类的领域之一。就域适应而言，从不同域源中提取特征及其相关意见词并将其映射到目标域是艰巨的任务。在本文中，对特征提取技术进行了改进，以增强映射任务。特征提取技术使用特征的句法和语义特性来提取相似词。通过合并同义词并用适当的反义词替换负极性术语，可以进一步完善功能。