ItemArticle

Spider Monkey Crow Optimization Algorithm with Deep Learning for Sentiment Classification and Information Retrieval

Title
Spider Monkey Crow Optimization Algorithm with Deep Learning for Sentiment Classification and Information Retrieval
Creator
Chugh A.; Sharma V.K.; Kumar S.; Nayyar A.; Qureshi B.; Bhatia M.K.; Jain C.
Description
The epidemic increase in online reviews' growth made the sentiment classification a fascinating domain in academic and industrial research. The reviews assist several domains, which is complicated to gather annotated training data. Several sentiment classification methodologies are devised for performing the sentiment analysis, but retrieval of information is not accurately performed, less effective, and less convergence speed. In this paper, we propose a sentiment paper proposes a sentiment classification model, namely Spider Monkey Crow Optimization algorithm (SMCA), for training the deep recurrent neural network (DeepRNN). In this method, the telecom review is employed to remove stop words and stemming to eliminate inappropriate data to minimize user's seeking time. Meanwhile, the feature extraction is performed using SentiWordNet to derive the sentiments from the reviews. The extracted SentiWordNet features and other features, like elongated words, punctuation, hashtag, and numerical values, are employed in the DeepRNN for classifying sentiments. To retrieve the required review, the Fuzzy K-Nearest neighbor (Fuzzy-KNN) is employed to retrieve the review based on a distance measure. With rigorous assessments and experimentation, it is observed that the proposed SMCA-based DeepRNN performs better in terms of accuracy of 97.7%, precision of 95.5%, recall of 94.6%, and F1-score 96.7%, respectively. 2013 IEEE.
Source
IEEE Access, Vol-9, pp. 24249-24262.
Date
2021-01-01
Publisher
Institute of Electrical and Electronics Engineers Inc.
Subject
deep recurrent neural network; fuzzy K-nearest neighbours; information retrieval; Sentiment classification; SentiWordNet
Coverage
Chugh A., Department of Computer Science and Engineering, Amity School of Engineering and Technology, Amity University, Gurugram, 122413, India; Sharma V.K., Faculty of Engineering and Technology, Jagannath University, Jaipur, 303901, India; Kumar S., Department of Computer Science and Engineering, CHRIST (Deemed to Be University), Bangalore, 560074, India; Nayyar A., Graduate School, Duy Tan University, Da Nang, 550000, Viet Nam, Faculty of Information Technology, Duy Tan University, Da Nang, 550000, Viet Nam; Qureshi B., Department of Computer Science, Prince Sultan University, Riyadh, 11586, Saudi Arabia; Bhatia M.K., Department of Computer Science, Jagan Institute of Management Studies, Delhi, 110085, India; Jain C., Department of Computer Science and Engineering, Amity School of Engineering and Technology, Amity University, Gurugram, 122413, India
Rights
All Open Access; Gold Open Access
Relation
ISSN: 21693536
Format
Online
Language
English
Type
Article

Collection

Articles

Citation

Chugh A.; Sharma V.K.; Kumar S.; Nayyar A.; Qureshi B.; Bhatia M.K.; Jain C., “Spider Monkey Crow Optimization Algorithm with Deep Learning for Sentiment Classification and Information Retrieval,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/16100.

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