@Article{JICS-15-113,
author = {Linjie Wu, Yujie Zheng and Yunfei Fan},
title = {A Pattern Recognition and Performance Index Evaluation Model of Football Team based on Principal Component Analysis and PageRank Algorithm},
journal = {Journal of Information and Computing Science},
year = {2020},
volume = {15},
number = {2},
pages = {113--123},
abstract = { With  the  increasing  knowledge  integration  and  task  complexity,  individual  ability  demands  a 
highly cohesive interdisciplinary team to amplify. To study the elements of successful team cooperation and 
explore valuable team strategies, this paper present a network pattern recognition model based on PageRank 
algorithm  and principal component analysis  method. Further, a team  cooperation performance  model based 
on  group  dynamic  theory  is  built  to  capture  the  individual  contribution  and  teamwork  characteristic  as  a 
supplementary evaluation. By applying the model into football competition, we found our model has 73.68% 
accuracy,  proving its outstanding adaptability. Based  on the  model,  we  can  get the information of the inner 
network  structure  of  a  team,  know  the  most  significant  contributors  pertinent  with  team  success,  and  make 
further justification plans and suggestions to achieve teamwork improvement. 
},
issn = {3080-180X},
doi = {https://doi.org/},
url = {http://global-sci.org/intro/article_detail/jics/22386.html}
}