related: Minor corrections
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@ -16,8 +16,8 @@ Finally, there are some surveys on application-specific privacy challenges.
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For example, Zhou et al.~\cite{zhou2008brief} have a focus on social networks, and Christin et al.~\cite{christin2011survey} give an outline of how privacy aspects are addressed in crowdsensing applications.
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In this chapter, we document works that deal with privacy under continuous data publishing covering diverse use cases.
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We present the works in the literature based on two levels of categorisation.
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First, we group works with respect to whether they receive microdata or statistical data (see Section~\ref{subsec:data-categories} for the definitions) as input.
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We present the works in the literature based on two levels of categorization.
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First, we group works with respect to whether they deal with microdata or statistical data (see Section~\ref{subsec:data-categories} for the definitions) as input.
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Then, we further group them into two subcategories, whether they are designed for the finite or infinite (see Section.~\ref{subsec:data-publishing}) observation setting. \kat{continue.. say also in which category you place your work}
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%Such a documentation becomes very useful nowadays, due to the abundance of continuously user-generated data sets that could be analyzed and/or published in a privacy-preserving way, and the quick progress made in this research field.
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\section{Summary}
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\label{sec:sum-rel}
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This is the summary of this chapter.
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In this chapter, we offer a guide that would allow its users to choose the proper algorithm(s) for their specific use case.
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\kat{? Don't forget to mention here the publication that you have.}
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