Abstract
Data are everywhere. Examples include sports data. Embedded in these data is implicit, previously unknown and potentially useful information or knowledge to be discovered. In this paper, we present a solution for sports data management, mining and visualization. In particular, we focus on basketball data. Basketball is a culture and is respected by fans around the world. Ever since its birth, basketball has changed drastically. Under such effects, basketball discussion and analysis evolved as well. Our solution adapts three different approaches for predicting the win. Evaluation on real-life basketball data show the effectiveness of our solution.
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Isichei, B. C., Leung, C. K., Nguyen, L. T., Morrow, L. B., Ngo, A. T., Pham, T. D., & Cuzzocrea, A. (2022). Sports Data Management, Mining, and Visualization. In Lecture Notes in Networks and Systems (Vol. 450 LNNS, pp. 141–153). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-99587-4_13
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