Abstract: Recently, analysing reviews presented by clients to products that are provided by e-commerce companies, such as Amazon, to produce efficient recommendations has been receiving a lot of attention. However, ensuring and generating effective recommendations on time is a challenge. This research paper proposes an artificial intelligence-based system. The proposed system uses the Incremental Learning - based Method (ILbM) to learn a neural network classifier. The ILbM uses the bagging technique in the process of training the classifier. To ensure a high degree of performance, the ILbM is implemented on the Hadoop since it allows the execution in parallel. Compared to a similar system, the proposed system shows better results in terms of accuracy (97.5%), precision (95.7%), recall (91.5%), and time of response (36 seconds).

Asma Alanazi and Marwan Alseid, “Artificial Intelligence based Recommendation System for Analyzing Social Bussiness Reviews” International Journal of Advanced Computer Science and Applications(IJACSA), 12(6), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0120614

@article{Alanazi2021,
title = {Artificial Intelligence based Recommendation System for Analyzing Social Bussiness Reviews},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0120614},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0120614},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {6},
author = {Asma Alanazi and Marwan Alseid}
}