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Argument Relevance Presentation
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Marc Feger
Argument Relevance Presentation
Commits
0c3b5cc5
Commit
0c3b5cc5
authored
4 years ago
by
Marc Feger
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Refactor slides/dataset.tex and master.tex
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master.tex
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-3
2 additions, 3 deletions
master.tex
slides/dataset.tex
+18
-37
18 additions, 37 deletions
slides/dataset.tex
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and
40 deletions
master.tex
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0c3b5cc5
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@@ -21,8 +21,7 @@
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@@ -21,8 +21,7 @@
\usepackage
{
mathabx
}
\usepackage
{
mathabx
}
\usepackage
[linesnumbered,algoruled,boxed,lined]
{
algorithm2e
}
\usepackage
[linesnumbered,algoruled,boxed,lined]
{
algorithm2e
}
\usepackage
{
amssymb
}
\usepackage
{
amssymb
}
\usepackage
[square,numbers]
{
natbib
}
\usepackage
[longnamesfirst, authoryear]
{
natbib
}
\usepackage
{
textcomp
}
\usepackage
{
textcomp
}
\usepackage
{
listings
}
\usepackage
{
listings
}
\usepackage
{
color
}
\usepackage
{
color
}
...
@@ -183,7 +182,7 @@ Department for Computer-Networks and Communication-Systems}
...
@@ -183,7 +182,7 @@ Department for Computer-Networks and Communication-Systems}
% % % % % % % % % Ende der eingefügten LaTeX-Dateien % % % % % % % % %
% % % % % % % % % Ende der eingefügten LaTeX-Dateien % % % % % % % % %
\begin{frame}
[allowframebreaks]
\frametitle
{
References
}
\begin{frame}
[allowframebreaks]
\frametitle
{
References
}
\bibliographystyle
{
abbrv
nat
}
\bibliographystyle
{
plain
nat
}
\bibliography
{
references
}
\bibliography
{
references
}
\nocite
{
*
}
\nocite
{
*
}
\end{frame}
\end{frame}
...
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slides/dataset.tex
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@@ -4,16 +4,10 @@
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@@ -4,16 +4,10 @@
\begin{frame}
\begin{frame}
\frametitle
{
Corpus
}
\frametitle
{
Corpus
}
\begin{itemize}
\begin{itemize}
\item
For our study, we used the Webis-ArgRank2017 dataset from Wachsmuth et
\item
For our study, we used the Webis-ArgRank2017 dataset by
\cite
{
wachsmuth:2017a
}
.
al.
\footnote
[1]
{
H. Wachsmuth, B. Stein, and Y. Ajjour "PageRank" for Argument
\item
Webis-ArgRank2017 contains a ground-truth argument graph
Relevance
}
as well as a benchmark for argument ranking
\item
In this dataset Wachsmuth et al. constructed a ground-truth argument graph
\item
The data was originally collected within the Argument-Web
as well as benchmark for argument ranking
\item
The data are originally collected from the Argument Web and stored in an
argument graph
\item
The Argument Web was the largest existing argument database with a
structured argument corpora at that time
\end{itemize}
\end{itemize}
\end{frame}
\end{frame}
...
@@ -22,17 +16,16 @@
...
@@ -22,17 +16,16 @@
\begin{itemize}
\begin{itemize}
\item
In the resulting argument graph G = (A, E)
\item
In the resulting argument graph G = (A, E)
\begin{itemize}
\begin{itemize}
\item
Each node represents
$
a
_
i
\in
A
$
an argument
consisting of a conclusion
\item
Each node represents
an argument
$
a
_
i
\in
A
$
consisting of a conclusion
$
c
_
i
$
and a not-empty set of premises
$
P
_
i
$
$
\Rightarrow
$
$
a
_
i
=
\langle
c
_
i, P
_
i
\rangle
$
$
c
_
i
$
and a not-empty set of premises
$
P
_
i
$
$
\Rightarrow
$
$
a
_
i
=
\langle
c
_
i, P
_
i
\rangle
$
\item
An edge
$
(
a
_
j, a
_
i
)
$
is given if the conclusion
$
a
_
j
$
is used as a premise
\item
An edge
$
(
a
_
j, a
_
i
)
$
is given if the conclusion
$
a
_
j
$
is used as a premise
of
$
a
_
i
$
of
$
a
_
i
$
\item
Consequently,
$
P
_
i
=
\{
c
_
1
,...,c
_
k
\}
, k
\geq
1
$
\item
Consequently,
$
P
_
i
=
\{
c
_
1
,...,c
_
k
\}
, k
\geq
1
$
\end{itemize}
\end{itemize}
\end{itemize}
\end{itemize}
\begin{figure}
\begin{figure}
\includegraphics
[width=0.
4
\linewidth]
{
bilder/DatasetLocalView2.png
}
\includegraphics
[width=0.
7
\linewidth]
{
bilder/DatasetLocalView2.png
}
\caption
{
Argument Graph from Argument Web
}
\caption
{
Part of the Argument-Web used to create Webis-ArgRank2017.
}
\end{figure}
\end{figure}
\end{frame}
\end{frame}
...
@@ -40,20 +33,16 @@
...
@@ -40,20 +33,16 @@
\subsection
{
Benchmark Argument Ranking
}
\subsection
{
Benchmark Argument Ranking
}
\begin{frame}
\begin{frame}
\frametitle
{
Benchmark Argument Ranking
}
\frametitle
{
Benchmark Argument Ranking
}
\cite
{
wachsmuth:2017a
}
kept those arguments fulfilling:
\begin{itemize}
\begin{itemize}
\item
To create the benchmark dataset, Wachsmuth et al. only kept arguments
\item
The conclusion was part in more than one argument
from the graph that fulfill their requirements
\item
Real claim
\begin{itemize}
\item
A conclusion must be part in more than one argument
\item
All nodes are removed that do not contain a
real claim
\item
Additionally, an argument:
\begin{itemize}
\item
has to be a valid-counter argument
\item
must be based on reasonable premises
\item
must allow a logic interference to be drawn
\end{itemize}
\end{itemize}
\end{itemize}
Additionally, an argument had to be:
\begin{itemize}
\item
a valid counterargument
\item
based on reasonable premises
\item
logically consistent
\end{itemize}
\end{itemize}
\end{frame}
\end{frame}
...
@@ -74,15 +63,7 @@
...
@@ -74,15 +63,7 @@
\begin{frame}
\begin{frame}
\frametitle
{
Evaluation Method
}
\frametitle
{
Evaluation Method
}
\begin{itemize}
\begin{itemize}
\item
Wachsmuth et al. used Kendall's
$
\tau
$
to evaluate the agreement between
\item
\cite
{
wachsmuth:2017a
}
used Kendall's
$
\tau
\in
[-
1
,
1
]
$
to evaluate the agreement between the experts and to ensure comparability
the experts and to ensure comparability
\item
The mean over all experts for the evaluation of the benchmark is
$
\tau
\approx
0
.
36
$
\item
Kendall
$
\tau
$
is a correlation coefficient that indicates the agreement
between two quantities with respect to a property
\begin{itemize}
\item
In this case, this means the agreement between two experts with respect to
an argument
\item
-1 signifies a complete disagreement and +1 a complete agreement
\end{itemize}
\item
The mean over all experts for the evaluation of the benchmark is 0.36
\end{itemize}
\end{itemize}
\end{frame}
\end{frame}
\ No newline at end of file
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