An Improved Method for Extractive Based Opinion Summarization Using Opinion Mining

作     者：Surbhi Bhatia Mohammed AlOjail 

作者机构：Department of Information SystemsCollege of Computer Sciences and Information TechnologyKing Faisal UniversitySaudi Arabia 

出 版 物：《Computer Systems Science & Engineering》 (计算机系统科学与工程（英文）)

年 卷 期：2022年第42卷第8期

页      面：779-794页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：to the Deanship of Scientific Research at King Faisal University for its financial support with reference to the research grant number as 216082 

主　　题：Sentiment analysis data mining text summarization opinion mining principal component analysis 

摘      要：Opinion summarization recapitulates the opinions about a common topic *** primary motive of summarization is to preserve the properties of the text and is shortened in a way with no loss in the semantics of the *** need of automatic summarization efficiently resulted in increased interest among communities of Natural Language Processing and Text *** paper emphasis on building an extractive summarization system combining the features of principal component analysis for dimensionality reduction and bidirectional Recurrent Neural Networks and Long Short-Term Memory(RNN-LSTM)deep learning model for short and exact synopsis using seq2seq *** presents a paradigm shift with regard to the way extractive summaries are *** algorithms for word extraction using assertions are *** semantic framework is well-grounded in this research facilitating the correct decision making process after reviewing huge amount of online reviews,considering all its important features into *** advantages of the proposed solution provides greater computational efficiency,better inferences from social media,data understanding,robustness and handling sparse *** on the different datasets also outperforms the previous researches and the accuracy is claimed to achieve more than the baselines,showing the efficiency and the novelty in the research *** comparisons are done by calculating accuracy with different baselines using Rouge tool.