\section{Workload Description}
\label{sec:data}

In our study, we analyze the workload of the video service of UOL, an important content provider in Brazil and Latin America.
The clickstream data obtained correspond to a period of almost one month, from 12/12/2007 a 01/07/2008, accounting for a total of 3,681,232 requests, from more than 1,127,537
different IPs.

\begin{table*}[hbt]
\begin{center}
%\scriptsize
\begin{tabular}{|c|l|r|c|}
\hline
Group Name & Request Type & Number of Requests & Percentage \\
\hline

1:View & View a video &  2,758,883 & 74.94\%  \\ \hline

% Usuário
\multirow{2}{*}{2:User} & Video list of a user  &  218.335    &  5,93\% \\ 
                   & Video list of a user with a certain tag &   75,583 &  2.05\% \\
\hline

% Listas
 \multirow{2}{*}{3:Lists} & List of top videos &   55,307   &  1.50\% \\
                    & List of related videos of a video & 32,838 &  0.89\%\\ 
\hline

% Interações
\multirow{3}{*}{4:Interactions} & Video evaluation & 22,038 &  0.60\% \\
& Video comment & 14,131 &  0.38\%  \\
& Favorite video & 10,774 &  0.29\% \\ 
\hline

%Busca
 \multirow{2}{*}{5:Search} & Search & 1,625 & 0.04\% \\ 
& List of videos with a certain tag    &  421,700    &  11.46\% \\ 
\hline

% Outros
 \multirow{2}{*}{6:Others} & Main page&  2,679 & 0.07\% \\ 
& Error requests or unformatted registry & 67,339 & 1.82\% \\ 
\hline
\end{tabular}
\end{center}
\caption{Request Groups}
\label{tab:tipos}
\end{table*}


Each registry on the workload represents a request sent by a user to the video service. The following information is available for each request: \textit{IP,
time, request, status, size, referrer, and agent}. The field \textit{IP} contains the anonymous IP address that generated the request. The field \textit{time}
corresponds to the moment, including date and time in seconds, in which the request was received by the server.  The field \textit{request} contains not only the URL requested, but
also the method and protocol used.  The field \textit{status} shows the HTTP protocol response code to the request. The field \textit{size} indicates the size
of the request in bytes. The field \textit{referrer} shows the URL from which the visiting request was originated. As an example, if a user on a Web page A
visits a link that redirects him/her to a video B, the field \textit{request} contains the URL B and the field \textit{referrer} contains the Web page A. The last
field, \textit{agent}, identifies the browser and operating system used. 

The fields \textit{referrer} and \textit{agent} can be missing in some registries, since users may remove
them to increase privacy. Additionally, the field \textit{referrer} can not occur when the user types the URL directly on the browser.

In our workload, there are several types of requests, which we organize into six groups, as shown in Table~\ref{tab:tipos}. The requests from group 1 correspond to 
video views. In group 2, we have requests related to list the videos of user and list the videos of a user that contain a certain tag. 
The third group joins user requests to lists of related videos and
lists of top videos. In group 4 we have all requests related to evaluate a video (assign a five-star rating) and user interactions related to include add a video as favorite and post a
comment to a video. Group 5 corresponds to requests for content search
through the video search engine or through accesses to a tag cloud. Error requests are identified through the field status, according to the definitions presented
in~\cite{rfc2616}. For the analysis of the next sections these requests are not considered. Except by group 6, all groups presented in Table~\ref{tab:tipos} are
used in the analysis of user navigation profile presented in Section~\ref{sub:models}.


\subsection{Limitations}

Although our data gives us a unique opportunity to study user activities across video sharing systems, the logs have several limitations. First, we are not able to identify the
user IDs in the system. Second, while we have information about the IP addresses of users, this information is anonymized. Thus, we are not able to associate a
distinct IP address with each user. This is because many residential ISPs use DHCP to dynamically assign an IP address to each host when it connects to the
Internet.  When a node disconnects, it releases its assigned IP address, which could then be assigned to a different residential customer. Therefore, we are not
able to group multiple sessions into events of a single user. Second, the fields \textit{referrer} and \textit{agent} may be missing in some registries of the log, since users can remove
them to preserve privacy. Finally, the field \textit{referrer} may be also missing when the user types the URL directly on the browser.







