Improved Metaheuristics with Deep Learning Enabled Movie Review Sentiment Analysis

作     者：Abdelwahed Motwakel Najm Alotaibi Eatedal Alabdulkreem Hussain Alshahrani MohamedAhmed Elfaki Mohamed K Nour Radwa Marzouk Mahmoud Othman 

作者机构：Department of Computer and Self DevelopmentPreparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Prince Saud AlFaisal Institute for Diplomatic StudiesRiyadhSaudi Arabia Department of Computer SciencesCollege of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer ScienceCollege of Computing and Information TechnologyShaqra UniversityShaqraSaudi Arabia Department of Computer SciencesCollege of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Information SystemsCollege of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer ScienceFaculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt 

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

年 卷 期：2023年第47卷第10期

页      面：1249-1266页

学科分类：0502[文学-外国语言文学] 050201[文学-英语语言文学] 05[文学] 

基　　金：Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2023R161) Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.The authors would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code:22UQU4340237DSR51) 

主　　题：Corpus linguistics sentiment analysis natural language processing deep learning word embedding 

摘      要：Sentiment Analysis(SA)of natural language text is not only a challenging process but also gains significance in various Natural Language Processing(NLP)*** SA is utilized in various applications,namely,education,to improve the learning and teaching processes,marketing strategies,customer trend predictions,and the stock *** researchers have applied lexicon-related approaches,Machine Learning(ML)techniques and so on to conduct the SA for multiple languages,for instance,English and *** to the increased popularity of the Deep Learning models,the current study used diverse configuration settings of the Convolution Neural Network(CNN)model and conducted SA for Hindi movie *** current study introduces an Effective Improved Metaheuristics with Deep Learning(DL)-Enabled Sentiment Analysis for Movie Reviews(IMDLSA-MR)*** presented IMDLSA-MR technique initially applies different levels of pre-processing to convert the input data into a compatible ***,the Term Frequency-Inverse Document Frequency(TF-IDF)model is exploited to generate the word vectors from the pre-processed *** Deep Belief Network(DBN)model is utilized to analyse and classify the ***,the improved Jellyfish Search Optimization(IJSO)algorithm is utilized for optimal fine-tuning of the hyperparameters related to the DBN model,which shows the novelty of the *** experimental analyses were conducted to validate the better performance of the proposed IMDLSA-MR *** comparative study outcomes highlighted the enhanced performance of the proposed IMDLSA-MR model over recent DL models with a maximum accuracy of 98.92%.