From 8c25d73f59d8c948fdf4e88a7860ec556207c799 Mon Sep 17 00:00:00 2001 From: "hannes.kuchelmeister" Date: Fri, 8 May 2020 12:10:30 +0200 Subject: [PATCH] fix caption --- 30_Thesis/sections/10_foundations.tex | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/30_Thesis/sections/10_foundations.tex b/30_Thesis/sections/10_foundations.tex index c7ecaf7..14721ce 100644 --- a/30_Thesis/sections/10_foundations.tex +++ b/30_Thesis/sections/10_foundations.tex @@ -147,7 +147,7 @@ Advantages and disadvantages of basic recommendation techniques are listed in \a \item No results \end{itemize} \\ \end{tabularx} - \caption{A description of the advantages and disadvantages of common recommendation techniques \cite{richthammerSituationAwarenessRecommender2018, shokeenStudyFeaturesSocial2019,hahslerRecommenderlabFrameworkDeveloping2015, aminiDiscoveringImpactKnowledge2011, suSurveyCollaborativeFiltering2009}} + \caption[Comparison of Recommendation Approaches]{A description of the advantages and disadvantages of common recommendation techniques \cite{richthammerSituationAwarenessRecommender2018, shokeenStudyFeaturesSocial2019,hahslerRecommenderlabFrameworkDeveloping2015, aminiDiscoveringImpactKnowledge2011, suSurveyCollaborativeFiltering2009}} \label{tab:Foundations:RecommenderComparison} \end{center} \end{table} @@ -186,7 +186,7 @@ Both the approach of merging preferences and the approach of using individual us average & $\frac{7}{3}$ & - & $\frac{10}{3}$ & $\frac{13}{3}$ & - \\ least misery & 1 & - & 2 & 3 & - \\ \end{tabular} - \caption{An example showing preference aggregation strategies for a group using the data from \autoref{tab:Foundations:RecommenderSystem:MoviePreferences}. Titanic and Wall-E were left out because not all group members have rated these movies.} + \caption[Movies: Result Matrix for Group Aggregation Strategies]{An example showing preference aggregation strategies for a group using the data from \autoref{tab:Foundations:RecommenderSystem:MoviePreferences}. Titanic and Wall-E were left out because not all group members have rated these movies.} \label{tab:Foundations:RecommenderSystem:AggregationStrategy} \end{table} @@ -200,7 +200,7 @@ He only makes changes to M.Customer which is renamed to M.Collab-Customer and in \begin{figure} \centering \includegraphics[width=0.6\textwidth]{./figures/20_fountations/MerlinCollaborativeConfigurator.pdf} - \caption{Architecture of Collaborative Configurator Merlin \cite[Fig. 4.3]{raabKollaborativeProduktkonfigurationEchtzeit2019}} + \caption[Architecture: Collaborative Configurator]{Architecture of Collaborative Configurator Merlin \cite[Fig. 4.3]{raabKollaborativeProduktkonfigurationEchtzeit2019}} \label{fig:Foundations:CollaborativeConfiguratorMerlin} \end{figure} @@ -210,7 +210,7 @@ The following list provides a short overview over each component. \item[M.Core] provides the base of the configurator. It checks the configuration against all rules in the database, provides possible alternatives if a change invalidates other parts of a configuration. The system relies on a CSP solver for validation and suggestion of alternatives. \item[M.Model] is the editor to create products and rules. These rules can then be uploaded to M.Core. \item[M.Collab] is a node.js server application that communicates with M.Core via REST-API and with M.Collab-Customer via WebSocket. It sits in between M.Collab-Customer and M.Core and handles all processing regarding collaborative configuration. - \item[M.Collab-Customer] ia a modified version of M.Customer that does all communication via WebSocket and does communicate with M.Collab instead of M.Core. M.Customer is the customer facing component. It allows a customer to configure a product or solution. + \item[M.Collab-Customer] is a modified version of M.Customer that does all communication via WebSocket and does communicate with M.Collab instead of M.Core. M.Customer is the customer facing component. It allows a customer to configure a product or solution. \end{description} \section{Software Design}