The Power and Precision of Journalistic Translation
Mr. Ardalan Hussein Awlla, a researcher at the Department of Computer Science, Cihan University Sulaimaniya, has published a significant article in the prestigious Journal of Electronic Commerce Research. The article introduces a novel Hybrid Self-Attention Layer Optimized Incentive Learning-based Collaborative Filtering-BiLSTM (Hybrid AT-IN based CF-BiLSTM) model designed for sentiment prediction and recommendation on e-commerce platforms.
This innovative model addresses crucial challenges in the field, such as data quality, data quantity, and the complexities of managing diverse scenes and languages in sentiment analysis. By integrating Collaborative Filtering (CF), Bidirectional Long Short-Term Memory (BiLSTM) networks, and a hybrid self-attention mechanism, the model achieves high precision and performance in predicting sentiment and making personalized recommendations.
Published in a Q1 journal with a CiteScore of 7.5 and an Impact Factor of 3.7, this research represents a major advancement in sentiment analysis and recommendation systems, contributing valuable insights to the field.
Article Link:
https://link.springer.com/article/10.1007/s10660-024-09888-5
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