Establishing an Assessment Recommender System to Measure Athletes' Satisfaction with Insurance Services Using Data Mining Techniques

The purpose of the present study was to Establishing an assessment recommender system to measure athletes' satisfaction with insurance services using Data Mining techniques. The method of this research is descriptive and is of survey type which is objective and applied in terms of collecting field information. The statistical population of the present study was athletes who regularly participated in sports in different sports in 2018, using Morgan and krejcie table 384 as a sample. The data collection tool was a researcher-made questionnaire whose validity was confirmed by 12 Sport management andinsurance specialists and its reliability was α = 0.86. The Kolmogorov-Smirnov test was used to normalize the data and Association Rules and apriori algorithm for classification and clustering of the algorithm. Data analysis was performed using SPSS version 23 and WEKA version 3.9.2. The findings showed that the most common injuries among athletes were upper limbs and dislocation. There is also a higher rate of injury in team disciplines. Results of satisfaction and ease of reimbursement of damages to insured athletes showed that athletes had moderate satisfaction with sports insurance services. as well as ensuring the most important component and accountability was the least important component in improving the satisfaction of athletes from insurance services. The results indicate that the number of athletes referring to the use of sports insurance plays an important role in the satisfaction of athletes with the services of the Sports Medical Federation.