Time Series Data Mining for Sport Data: a Review

Q2 Computer Science
Rumena Komitova, Dominik Raabe, R. Rein, D. Memmert
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引用次数: 1

Abstract

Abstract Time series data mining deals with extracting useful and meaningful information from time series data. Recently, the increasing use of temporal data, in particular time series data, has received much attention in the literature. Since most of sports data contain time information, it is natural to consider the temporal dimension in form of time series. However, in sports, the effective use of time series data mining techniques is still under development. The main goal of this paper is therefore to serve as an introduction to time series data mining and a glossary for interested researchers from the sports community. The paper gives an overview about current data mining tasks and tries to identify their potential research direction for further investigation. Furthermore, we want to draw more attention with respect to the importance of mining approaches with sport data and their particular challenges beyond usual time series data mining tasks.
体育数据的时间序列数据挖掘研究综述
时间序列数据挖掘是从时间序列数据中提取有用的、有意义的信息。近年来,越来越多地使用时间数据,特别是时间序列数据,在文献中受到了广泛的关注。由于大多数体育数据都包含时间信息,所以自然会以时间序列的形式来考虑时间维度。然而,在体育领域,时间序列数据挖掘技术的有效利用仍在开发中。因此,本文的主要目标是为体育界感兴趣的研究人员提供时间序列数据挖掘的介绍和术语表。本文概述了当前的数据挖掘任务,并试图确定其潜在的研究方向,以进一步研究。此外,我们希望更多地关注体育数据挖掘方法的重要性,以及它们在常规时间序列数据挖掘任务之外的特殊挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
International Journal of Computer Science in Sport
International Journal of Computer Science in Sport Computer Science-Computer Science (all)
CiteScore
2.20
自引率
0.00%
发文量
4
审稿时长
12 weeks
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