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30_Thesis/sections/60_evaluation.tex
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@@ -174,8 +174,6 @@ These user profiles can be used to generate rather homogenous groups but also to
\end{center} \end{center}
\end{table} \end{table}
\todo[inline]{explain preference profiles} \todo[inline]{explain preference profiles}
\section{Hypotheses} \section{Hypotheses}
@@ -184,22 +182,16 @@ These user profiles can be used to generate rather homogenous groups but also to
Understanding data is made easier by first posing hypothesises. This section gives an overview over the hypothesis used during data analysis. Understanding data is made easier by first posing hypothesises. This section gives an overview over the hypothesis used during data analysis.
\begin{enumerate}[font={\bfseries},label={H\arabic*}] \begin{enumerate}[font={\bfseries},label={H\arabic*}]
\item More homogeneous groups have more satisfied members with the recommender's decision but also with the dictator's decision compared to less homogeneous groups. \item Highest improvements with group recommendation are when the amount of people satisfied with the dictators decision is slightly lower than two. Respectively that holds true for dissatisfaction.
\item More heterogeneous groups see a bigger increase in satisfaction than less heterogeneous groups when comparing the dictator's decision with the recommender's decision. \item A higher $tc$ value results in less satisfied people and more unsatisfied people with regard to the dictator's decision.
\item A higher $tc$ value results in less satisfied people and more unsatisfied people.
\item There exists a $tc$ value which causes only one person to be satisfied with the dictator's decision and no one is satisfied with the group recommender's decision. \item There exists a $tc$ value which causes only one person to be satisfied with the dictator's decision and no one is satisfied with the group recommender's decision.
\item A higher amount of stored finished configurations results in a better recommendation result. \item Homogeneous groups have more satisfied members with the recommender's decision but also with the dictator's decision compared to heterogeneous groups.
\item More heterogeneous groups see a bigger satisfaction increase than less heterogeneous groups when comparing the dictator's decision with the recommender's decision.
\item A higher amount of stored finished configurations results in a higher amount of satisfied and a lower amount of dissatisfied group member.
\item \label{hyp:Evaluation:LowSMD} A low $smd$ results in more people being satisfied and in more people being dissatisfied. This is expected due to the increase of configurations that fall in the specified quantiles. \item Multiplication and best average aggregation strategies perform better than least misery. % These strategies are listed by \citeauthor{Masthoff2015} \cite[p. 755f]{Masthoff2015} and multiplication and best average came out as the best in most studies. Least misery was in some listed as performing worst. Therefore it fares worse than the other strategies here.
\item \label{hyp:Evaluation:HighSMD} A high $smd$ results in less people being satisfied and in less people being dissatisfied. This is expected due to the decrease of configurations that fall in the specified quantiles.
\item \label{hyp:Evaluation:MoreSatisfiedLessIncrease} More people being satisfied results in a lower increase of satisfaction due to most people being satisfied already.
\item \label{hyp:Evaluation:OnePersonSatisfied} A too high $smd$ results in a negative satisfaction and therefore in a satisfaction change of minus one. This is caused because only one person, the person who made the individual decision, is satisfied with it.
\item \label{hyp:Evaluation:NoOnedissatisfied} A too high $smd$ results in no decrease in dissatisfied people when comparing the group decision with the individual decision.
\item \label{hyp:Evaluation:NumberOfStored} More stored finished configurations results in a higher increase in satisfaction and a higher reduction in dissatisfied group members.
\item \label{hyp:Evaluation:AggregationFunctions} Multiplication and best average aggregation strategies should perform better than least misery. These strategies are listed by \citeauthor{Masthoff2015} \cite[p. 755f]{Masthoff2015} and multiplication and best average came out as the best in most studies. Least misery was in some listed as performing worst. Therefore it fares worse than the other strategies here.
\end{enumerate} \end{enumerate}
\todo[inline]{explain hypotheses}
\section{Findings} \section{Findings}
\label{sec:Evaluation:Findings} \label{sec:Evaluation:Findings}