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hannes.kuchelmeister
2020-03-17 11:02:33 +01:00
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30_Thesis/sections/40_concept.tex
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@@ -88,7 +88,7 @@ The used characteristics and attributes are shown in \autoref{fig:Concept:Forest
\section{Solution Generation}
\label{sec:Concept:SolutionGeneration}
Given an unfinished configuration and preferences of all group members, rate a finished configuration on how well it reflects the configuration state and preferences. This Use this to choose the best finished configuration out of a list to recommend.
Given an unfinished configuration and preferences of all group members, rate a finished configuration on how well it reflects the configuration state and preferences. Use this to choose the best finished configuration out of a list to recommend.
\subsection{Generating a Recommendation}
@@ -131,7 +131,7 @@ An example group configuration scoring function is $score_{group}$ with
\end{split}
\end{equation}
This thesis will use multiple scoring functions. Among those are ones for least misery, average and multiplicative. Average and multiplicative yield good results among the studies presented by \citeauthor{Masthoff2015}. Strategies can also be combined, one example here is average without misery \cite{Masthoff2015}.
This thesis will use multiple scoring functions. Among those are ones for least misery, average and multiplicative. Average and multiplicative yield good results among the studies presented by \citeauthor{Masthoff2015} \cite{Masthoff2015}. Strategies can also be combined, one example here is average without misery.
\end{samepage}
\subsubsection{Preference Scoring}