An Intelligent Cognitive-Inspired Computing with Big Data Analytics Framework for Sentiment Analysis and Classification

作者：

Highlights：

• A Binary Brain Storm Optimization (BBSO) algorithm is being used for the Feature Selection (FS) process and thereby achieving improved classification performance.

• A Fuzzy Cognitive Maps (FCMs) are used as a classifier to classify the incidence of positive or negative sentiments.

• The experimental values highlights the improved classification performance of the proposed BBSO-FCM model in terms of different measures.

摘要

•A Binary Brain Storm Optimization (BBSO) algorithm is being used for the Feature Selection (FS) process and thereby achieving improved classification performance.•A Fuzzy Cognitive Maps (FCMs) are used as a classifier to classify the incidence of positive or negative sentiments.•The experimental values highlights the improved classification performance of the proposed BBSO-FCM model in terms of different measures.

论文关键词：Cognitive Computing,Big data analytics,Hadoop Map Reduce,Sentiment Analysis,Feature selection,Intelligent models,Classification

论文评审过程：Received 18 June 2021, Revised 3 September 2021, Accepted 8 September 2021, Available online 22 September 2021, Version of Record 22 September 2021.

论文官网地址：https://doi.org/10.1016/j.ipm.2021.102758