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-*.out
-*.aux
-*.gz
-*.log
-*.toc
diff --git a/thesis/tex/Chapter/alg_overview.tex b/thesis/tex/Chapter/alg_overview.tex
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-\tikzstyle{block} = [rectangle, draw, fill=blue!20, 
-    text width=5em, text centered, rounded corners, minimum height=4em]
-\tikzstyle{line} = [draw, -latex']
-
-\begin{figure}[h]
-
-\begin{tikzpicture}[node distance = 1cm]
-    \node [block] (datamodel) {Data Modeling};
-    \node [block, left=  of datamodel] (input) {Input};
-    \node [block, below= of datamodel] (reduce) {Reduction Rules};
-    \node [block, below right = of reduce] (solveILP) {ILP Solver};
-    \node [block, below left = of reduce] (solveHeuristic) {Heuristic Solver};
-    \node [block, below right= of solveHeuristic] (output) {Generate Output};
-
-	\path [line] (input) -- (datamodel);
-    \path [line] (datamodel) -- (reduce);
-		\path [line] (reduce) -- (solveILP);
-		\path [line] (reduce) -- (solveHeuristic);
-	\path [line] (solveILP) -- (output);
-	\path [line] (solveHeuristic) -- (output);
-
-	 
-\end{tikzpicture}
-
-	\caption{Overview of the Yoshiko Algorithm}  \label{algOverview}
-
-
-\end{figure}
-ROUGH IDEA:
-COMPLETE GRAPH, CHOOSE EDGES SO THAT sum of C(E) is MAX while satisfying Triangle inequalities > Fully Disjunct Clique-Graph
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diff --git a/thesis/tex/Chapter/dm_impl.tex b/thesis/tex/Chapter/dm_impl.tex
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-The Yoshiko Wrapper provides a clean and simple interface to generate the model.
-\subparagraph{Mapping edge costs}
-The user has the possibility to use a numeric Cytoscape column of the node table as a source for the edge-cost function $C$.
-\subparagraph{Insertion and deletion cost}
-The default values $C_I$ and $C_D$ can be set by the user with the default values being $C_I=-1$ and $C_D=1$.
-It should be noted, that the insertion cost value is not normalized or in any way adjusted when a mapping is used. This means that the user needs to adjust this value wisely to fit the data.
-As an example the user might have mapped the edge costs to a column containing values in the range of $10^6-10^7$.
-The default insertion cost of $-1$ will be irrelevant in comparison and the algorithm will most likely insert all missing edges and generate one big cluster as a solution.
-Overall the ratio $R = \frac{|C_I|}{C_D}$ should give you a rough idea how the algorithm will operate.\\
-$R > 1$ means, that the algorithm is more likely to delete edges to generate cliques, a value of $R<1$ means insertions are more likely.
-\subparagraph{Mapping permanent or forbidden edges}
-The Yoshiko app has additional convenience functions:
-The user can map edges to a boolean Cytoscape column to mark them as either 
-\textbf{forbidden} (meaning that those edges will never be part of the solution) or
-\textbf{permanent} (meaning that those edges will always be part of the solution).
-Marking an edge e as forbidden is equivalent to $C(e)=-\infty$,
-marking an edge e as permanent is equivalent to $C(e)=\infty$.
-This way the user is able to apply expert knowledge about the input instance to increase the quality of the solution.
-
-
diff --git a/thesis/tex/Chapter/dm_theory.tex b/thesis/tex/Chapter/dm_theory.tex
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--- a/thesis/tex/Chapter/dm_theory.tex
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-
-The Yoshiko algorithm models the data as a complete graph
-$G=(V,E)$ 
-with an associated edge-cost function 
-$C: E \rightarrow \mathbb{R} 
-\cup \lbrace -\infty \rbrace 
-\cup \lbrace \infty \rbrace $.
-As many input instances do not describe a full graph, missing edges and costs need to be modeled.
-This is achieved by using default values for insertion or deletion.
-A default insertion cost $C_I \in [-\infty,0]$ is used as $C(e)$ whenever the input instance does not contain an edge $e$.
-A default deletion cost  $C_D \in [0,\infty ]$ is used as $C(e)$ whenever the input instance does contain an edge $e$ that has no cost associated yet.
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diff --git a/thesis/tex/Multigraph.pdf b/thesis/tex/Multigraph.pdf
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diff --git a/thesis/tex/Multigraph.tex b/thesis/tex/Multigraph.tex
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@@ -1,12 +0,0 @@
-\documentclass[10pt,a4paper]{article}
-\usepackage[utf8]{inputenc}
-\usepackage[english]{babel}
-\usepackage{amsmath}
-\usepackage{amsfonts}
-\usepackage{amssymb}
-\author{Philipp Spohr}
-\title{Rough Analysis of Cluster Editing Reduction Rules in Multi-Graphs}
-\begin{document}
-\maketitle
-\section{•}
-\end{document}
\ No newline at end of file
diff --git a/thesis/tex/Thesis.pdf b/thesis/tex/Thesis.pdf
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diff --git a/thesis/tex/Thesis.tex b/thesis/tex/Thesis.tex
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-\documentclass[10pt,a4paper]{article}
-
-\usepackage[utf8]{inputenc}
-\usepackage[english]{babel}
-\usepackage{amsmath}
-\usepackage{amsfonts}
-\usepackage{amssymb}
-\usepackage{abstract}
-\usepackage{hyperref}
-\usepackage{graphicx}
-\usepackage{tikz}
-\usepackage{verbatim}
-\usepackage{float}
-
-\usetikzlibrary{shapes,arrows}
-\usetikzlibrary{positioning}
-
-\hypersetup{
-    linktoc=all
-}
-
-\author{Philipp Spohr}
-
-\title{Developing and evaluating a Cytoscape app for graph-based clustering}
-
-\begin{document}
-
-\maketitle
-
-\cleardoublepage
-
-\begin{abstract}
-This paper describes an implementation of the Yoshiko-alorithm,
-which clusters data based on the weighted cluster-editing problem,
-as a plugin for Cytoscape.
-
-Cytoscape is a network visualization and analysis tool (insert info)
-
-Yoshiko is based on work from (insert info)
-
-
-\end{abstract}
-
-\tableofcontents
-
-\clearpage
-
-\section{Introduction}
-\section{The Yoshiko-App for Cytoscape}
-	\subsection{Technical Details}
-		\subsubsection{Program Structure}
-		\subsubsection{JNI}
-	\subsection{Algorithm}
-		\input{Chapter/alg_overview}
-		\subsubsection{Data Modeling}
-			\paragraph{Theory}
-			\input{Chapter/dm_theory}
-			\paragraph{Implementation}
-			\input{Chapter/dm_impl}
-\section{Evaluation of the Yoshiko Algorithm}
-\section{Outlook}
-	\subsection{Multigraph Analysis}
-	\subsection{Integration in other frameworks}
-\end{document}
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