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@@ -7,22 +7,35 @@
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\end{center}
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\end{frame}
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-\begin{frame}{Der Algorithmus}
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-\begin{algorithm}[H]
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- \begin{algorithmic}
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- \Function{DYCOS}{Network $G_t = (N_t, A_t, T_t), l, h, p_s$}
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- \ForAll{node $v$ in $T_t$} \Comment{Für jeden gelabelten Knoten}
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- \For{$i \in 1, \dots, l$}
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- \State Perform an $h$-hop random walk from $v$
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- \EndFor
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- \State Classify $v$ with the class labels most frequent
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- encountered
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- \EndFor
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- \EndFunction
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- \end{algorithmic}
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-\caption{DYCOS algorithm for classification with content and structure}
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-\label{alg:seq1}
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-\end{algorithm}
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+\begin{frame}{DYCOS}
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+ DYCOS zeichnet sich aus durch:
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+ \begin{itemize}
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+ \item \textbf{Geschwindigkeit}: < $10\si{\second}$ für
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+ \begin{itemize}
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+ \item $806\,635$ Knoten ($18\,999$ mit Labels)
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+ \item $4\,414\,135$ Kanten
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+ \end{itemize}
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+ \item \textbf{Genauigkeit}: > $65\%$
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+ \end{itemize}
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\end{frame}
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+%\begin{frame}{Der Algorithmus}
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+%\begin{algorithm}[H]
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+% \begin{algorithmic}
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+% \Function{DYCOS}{Network $G_t = (N_t, A_t, T_t), l, h, p_s$}
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+% \ForAll{node $v$ in $T_t$} \Comment{Für jeden gelabelten Knoten}
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+% \For{$i \in 1, \dots, l$}
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+% \State Perform an $h$-hop random walk from $v$
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+% \EndFor
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+% \State Classify $v$ with the class labels most frequent
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+% encountered
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+% \EndFor
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+% \EndFunction
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+% \end{algorithmic}
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+%\caption{DYCOS algorithm for classification with content and structure}
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+%\label{alg:seq1}
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+%\end{algorithm}
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+%\end{frame}
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+
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+
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