Artificial Intelligence based Recommendation System for Analyzing Social Bussiness Reviews
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 p...
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| Veröffentlicht in: | International journal of advanced computer science & applications 2021, Vol.12 (6) |
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| container_title | International journal of advanced computer science & applications |
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| creator | Alanazi, Asma Alseid, Marwan |
| description | 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). |
| doi_str_mv | 10.14569/IJACSA.2021.0120614 |
| format | Article |
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| subjects | Artificial intelligence Classifiers Neural networks Recommender systems |
| title | Artificial Intelligence based Recommendation System for Analyzing Social Bussiness Reviews |
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