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% The following data (volume, number and page) are given by the editors prior to publishing your article
\jidmVolume{3}
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\jidmYear{12}
\jidmMonth{October}
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%\alignauthor P{\'e}terson S. Proc{\'o}pio Jr, Marcos A. Gon\c{c}alves,  Alberto H. F. Laender, Thiago Salles,\\ Daniel Figueiredo$^\ddagger$\\
% Includes headers with simplified name of the authors and article title
%\markboth{P. S. Proc{\'o}pio Jr and M. A. Gon\c{c}alves and A. H. F. Laender and T. Salles and D. Figueiredo}
%{Time-Aware Ranking in Sport Social Networks}
\markboth{P{\'e}terson S. Proc{\'o}pio Jr et. al.}
{Time-Aware Ranking in Sport Social Networks}

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%         ex: \markboth{M. M. Moro}{Any article title}


% Title of the article
\title{Time-Aware Ranking in Sport Social Networks}


% List of authors
%IF THERE ARE TWO or more institutions, please use:
%\author{Name of Author1\inst{1}, Name of Author2\inst{2}, Name of Author3\inst{2}}
\author{P{\'e}terson S. Proc{\'o}pio Jr$^{1}$, Marcos A. Gon\c{c}alves$^{1}$,  Alberto H. F. Laender$^{1}$, Thiago Salles$^{1}$,\\ Daniel Figueiredo$^{2}$}


%Affiliation and email

\institute{Departamento de Ci{\^e}ncia da Computa\c{c}{\~a}o \\ Universidade Federal de Minas Gerais, Brazil \\ \email{\{peterson,mgoncalv,laender,tsalles\}@dcc.ufmg.br}
\and Programa de Engenharia de Sistemas e Computa\c{c}{\~a}o \\ Universidade Federal do Rio de Janeiro, Brazil \\
\email{daniel@land.ufrj.br}
% IF THERE IS ANOTHER INSTITUTION:
%\and Name_of_the_second_institution \\
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}

% Article abstract - it should be from 100 to 300 words
\begin{abstract}
Sport social networks concern different types of relationship among athletes or teams in specific sports. 
Such networks have recently been used to address problems related to prediction of results of matches or 
championships and rankings of athletes or teams. In many cases, such analyses consider a complete and static 
view of the network that does not take into account the temporal nature of sports events. In this article, we 
present a time-aware ranking method for sport social networks that explicitly considers these temporal factors. 
In particular, we propose modeling such networks with edge weights that decay over time, in order to 
represent the relative importance of past interactions. We apply the proposed method to two sports, namely Mixed Martial Arts (MMA) and tennis. Our results show that our rankings are more accurate than a baseline ranking that ignores temporal factors, when both are compared to gold standards derived from well known rankings.
\end{abstract}

% ACM Computing Classification System categories
\category{J.4}{Computer Applications}{Social and Behavioral Sciencies}
%\category{H.3}{Information Storage and Retrieval}{Miscellaneous}
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% Article keywords
\keywords{Complex Networks, Sport Social Networks, Temporal Factors} 
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This work was partially funded by InWeb - The Brazilian National Institute of Science and Technology
for the Web (grant MCT/CNPq 573871/2008-6), and by the authors' individual grants from CNPq and FAPEMIG. The authors would also like to thank Filippo Radicchi for his assistance in their experiments.
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\maketitle



\input{introduction.tex}

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\input{conclusion.tex}


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