Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Spider Monkey Crow Optimization Algorithm with Deep Learning for Sentiment Classification and Information Retrieval Subject The topic of the resource deep recurrent neural network; fuzzy K-nearest neighbours; information retrieval; Sentiment classification; SentiWordNet Description An account of the resource 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. Creator An entity primarily responsible for making the resource Chugh A.; Sharma V.K.; Kumar S.; Nayyar A.; Qureshi B.; Bhatia M.K.; Jain C. Source A related resource from which the described resource is derived IEEE Access, Vol-9, pp. 24249-24262. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2021-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ACCESS.2021.3055507" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ACCESS.2021.3055507</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100446997&amp;doi=10.1109%2FACCESS.2021.3055507&amp;partnerID=40&amp;md5=5421afa26c8899d6b4ae87187b1fd302" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100446997&amp;doi=10.1109%2fACCESS.2021.3055507&amp;partnerID=40&amp;md5=5421afa26c8899d6b4ae87187b1fd302</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 21693536 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant 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