ISSN 1000-1239 CN 11-1777/TP

计算机研究与发展 ›› 2016, Vol. 53 ›› Issue (12): 2729-2752.doi: 10.7544/issn1000-1239.2016.20160568

• 其他应用技术 • 上一篇    下一篇

基于GraphX的传球网络构建及分析研究

张陶1,于炯1,廖彬2,国冰磊1,卞琛1,王跃飞1,刘炎3   

  1. 1(新疆大学信息科学与工程学院 乌鲁木齐 830046); 2(新疆财经大学统计与信息学院 乌鲁木齐 830012); 3(清华大学软件学院 北京 100084) (zt59921661@126.com)
  • 出版日期: 2016-12-01
  • 基金资助: 
    国家自然科学基金项目(61562078,61262088,71261025);新疆维吾尔自治区自然科学基金项目(2016D01B014)

The Construction and Analysis of Pass Network Graph Based on GraphX

Zhang Tao1, Yu Jiong1, Liao Bin2, Guo Binglei1, Bian Chen1, Wang Yuefei1, Liu Yan3   

  1. 1(School of Information Science and Engineering, Xinjiang University, Urumqi 830046); 2(School of Statistics and Information, Xinjiang University of Finance and Economics, Urumqi 830012); 3(School of Software, Tsinghua University, Beijing 100084)
  • Online: 2016-12-01

摘要: 虽然大数据技术在社交网络、金融、公共安全、医疗卫生等领域的应用不断成熟,但在竞技体育方面的应用还处于探索阶段.常规篮球统计中缺乏对传球数据的记录,更缺乏对传球数据的统计分析、价值挖掘及应用等方面的研究.1)由于传球数据汇聚形态为图,在传球数据获取、数据清洗及格式转化、Vertex与Edge表构建的基础上,通过GraphX构建传球网络图为其应用打下基础;2)提出PlayerRank值区分球员重要度、球员位置个性化图顶点等方法提高传球网络可视化质量;3)通过GraphX构建的传球网络分析传球数量与质量对比赛结果的影响,并例举了传球网络在球队传球数据分析、战术人员选择、临场战术制定、网络子图及游戏体验改进等方面的应用.

关键词: 大数据应用, 传球网络, GraphX框架, PlayerRank算法, 球员重要性

Abstract: In the field of social networking, finance, public security, health care, etc, the application of big data technology is matured constantly, but its application in competitive sports is still in exploratory stage. Lacking of recording the pass data in basketball technical statistics leads that we can not research the statistical analysis, data mining and application on the pass data. Firstly, as the aggregation from of passing data is graph, based on data acquisition, clean and format conversion, Vertex and Edge table construction, we create the pass network graph with GraphX, which lays the foundation for other applications. Secondly, the PlayerRank algorithm is proposed to distinguish the importance of players, player position personalized the graph vertex’s color, etc, which improves the visual quality of pass network graph. Finally, we can use the pass network graph created by GraphX to analyze the effect of passing quantity and quality on the outcome of the game, and the pass network graph is also used to analyze the team’s passing data, tactical player selection, on-the-spot tactics supporting, subgraph extraction and gaming experience improvement, etc.

Key words: big data application, pass network, GraphX frame, PlayerRank algorithm, player importance

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