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Recommender systems now tend to gain popularity and significance. The proliferation of many recommender systems leads to the difficulty of locating a good recommender system. The algorithms contained in the recommender system determine the efficiency of the recommender systems. The question now is to find the most appropriate algorithms to meet users' needs. So far, the research carried out has focused...
Collaborative filtering technology has been successfully used in personalized recommendation systems. With the development of E-commerce, as well as the increase in the number of users and items, the users score data sparsity and the dimension disaster problems have been caused which leads to sharp decline in the quality of their recommend. A calculation of pattern similarity was proposed based on...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.