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Recommendation Systems has emerged as an essential component in web-based systems, as their ability to analyze customers' behavior and generate recommendations seeking customers' satisfaction is successfully accomplished. However, the success of these systems depends on amount of customers' personal preference data and content (items') metadata available for harnessing. Therefore, data sparsity poses a major challenge here. To alleviate this problem, data and models from other domains can bedoi:10.25103/jestr.113.12 fatcat:2mxouuj2zfdjffk3nwb5lj4v4u