Aspect extraction represents a core task of aspect-based sentiment analysis. This study presents a supervised aspect extraction algorithm for explicit aspect extraction from formal and informal texts. To accomplish the new algorithm, 126 aspect extraction rules are combined to cover both formal and informal texts, because customer reviews are a mix of formal and informal texts. These 126 rules include certain dependency-based rules and pattern-based rules from previous studies, in addition to newly developed rules intended to overcome prior rules’ weaknesses. In addition, many aspect extraction rules have remained unexplored by previous studies. However, many of these 126 rules are irrelevant and should be removed. Thus, a prober selection of the included rules is required. Therefore, in this study we also improved the Whale Optimization Algorithm (WOA) to address rules selection problem with an improved algorithm called improved WOA (IWOA). Two major improvements were included into IWOA. The first improvement is the development of a new update equation based on Cauchy mutation to improve WOA population diversity. The second improvement is the development of a new local search algorithm (LSA) to solve WOA local optima. The IWOA algorithm is applied on the full set of rules to select best rules subset and remove low quality rules. Finally, a new pruning algorithm (PA) has been developed to remove incorrect aspects and retain correct aspects. The Results on seven benchmark datasets demonstrate that IWOA+PA outperforms all other state-of-the-art baseline works and most recent works.

方面提取是基于方面的情感分析的核心任务。这项研究提出了一种监督方面的提取算法，用于从正式和非正式文本中显式提取方面。为了完成新算法，合并了126个方面的提取规则以涵盖正式和非正式文本，因为客户评论是正式和非正式文本的混合体。这126条规则除了旨在克服先前规则的弱点的新开发规则之外，还包括先前研究中的某些基于依赖项的规则和基于模式的规则。另外，以前的研究还没有探索许多方面提取规则。但是，这126条规则中的许多都是不相关的，应删除。因此，需要对包括的规则进行探针选择。因此，在这项研究中，我们还通过一种称为改进WOA（IWOA）的改进算法改进了鲸鱼优化算法（WOA）以解决规则选择问题。IWOA包含两项重大改进。第一项改进是开发基于柯西突变的新更新方程，以改善WOA种群多样性。第二个改进是开发了一种新的局部搜索算法（LSA），以解决WOA局部最优问题。IWOA算法应用于整个规则集，以选择最佳规则子集并删除低质量规则。最终，开发了一种新的修剪算法（PA），以删除不正确的方面并保留正确的方面。七个基准数据集上的结果表明，IWOA + PA的性能优于所有其他最新基准工作和最新工作。