remove hybrid recommender

30_Thesis/sections/10_foundations.tex

@@ -8,7 +8,7 @@ This chapter gives an overview of the foundations this thesis is based upon. It
 
 A recommender system is a system that gives individualized recommendations to users to guide them through a large space of objects \cite[~ p. 331]{burkeHybridRecommenderSystems2002}.
 
-There are several approaches to recommender systems presented in \cite{felfernigGroupRecommenderSystems2018}, some of them are: collaborative filtering, constraint-based recommendation, content-based filtering and hybrid recommendation.
+There are several approaches to recommender systems presented in \cite{felfernigGroupRecommenderSystems2018}, some of them are: collaborative filtering, constraint-based recommendation and content-based filtering. There is also hybrid recommendation which combines approaches but this is not the focus in this thesis.
 
 \subsection{Collaborative Filtering}
 
@@ -135,9 +135,6 @@ Last, content-based filtering does not depend on historic group preference accur
 
 In constrained-based recommendation approaches it is possible that constraints lead to no possible solution \cite[~ p. 44]{felfernigAlgorithmsGroupRecommendation2018}. This then requires further techniques of constrained relaxing and a user is faced with the situation that they have to search for constraints which fulfil less strict requirements. Moreover, in groups a constraint-based approach has to deal with contrary user constraints. Therefore, diverse groups could have issues with it.
 
-\subsection{Hybrid Recommendation}
-A hybrid recommender combines different recommendation approaches to use the strengths of each individual one and to reduce effects of weaknesses \cite{burkeHybridRecommenderSystems2002}.
-
 \section{Group Recommender System}
 \label{sec:Foundations:GroupRecommenderSystem}