Designing a personalized gamification social network platform using machine algorithms (clustering) (use case: user suggestion for doing data science learning projects in work teams)
نویسندگان
1 Faculty of Management and Accounting, Qazvin Branch, Islamic Azad University, Qazvin, Iran
2 Faculty of Management and Accounting, Qazvin Branch, Islamic Azad University, Qazvin, Iran
3 School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
doi
10.22075/ijnaa.2023.31702.4701چکیده
The role of social media is undeniable, important and influential in today's world. The Var game emphasizes using game design elements in non-game fields, a concept that will reach a value of 5.5 million dollars in 2018, based on the predictions made. One of the applications in which gamification has been used is in the field of better learning and cooperation. One of the mistakes in the design of game elements is having the same content creation strategy for all users. In this personal gamification article, based on specific specifications and features, suitable teams are suggested to people to carry out data mining projects on the designed platform. One of the ways to personalize the game is to use machine algorithms (data mining). The main goal of this article is to improve the design of the personalized gaming social network platform using unsupervised clustering machine algorithms to carry out personalized gaming data science projects in this field using unsupervised algorithms.
