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Utilizing Mining Techniques for Attributes' Intra-Relationship Detection, a Collaborative Approach
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AI
DOI：10.1080/10447318.2022.2112029.png)
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Abstract
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In this research, a set of data mining techniques are applied to target to balance between the industry requirement and user satisfaction. The proposed approach aims at exploring the most significant attributes for the industry services' evaluation. The exploration goal ensures a double-sided benefit for both the industry and the user. From one perspective, it raises the evaluation accuracy level for the main service's attributes which is most important to the user and consequently leads to higher user satisfaction. On the other side, it minimizes the user's collaboration effort in the evaluation process which raises the user's collaboration willingness. The proposed approach has been applied to the IoT services industry in Saudi Arabia. The results proved that eliminating insignificant attributes has provided minimal user effort with retaining the required evaluation accuracy and the success percentage reached 90%.
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