diff --git a/dissertation/dissertation.pdf b/dissertation/dissertation.pdf index 9d64b52..9a688fe 100644 Binary files a/dissertation/dissertation.pdf and b/dissertation/dissertation.pdf differ diff --git a/dissertation/dissertation.tex b/dissertation/dissertation.tex index 47d97e0..ad44c3d 100644 --- a/dissertation/dissertation.tex +++ b/dissertation/dissertation.tex @@ -193,7 +193,7 @@ outliers, or even maximise temporal communities. \chapter{Topological Data Analysis and Persistent Homology}% \label{cha:tda-ph} -\section{Basic constructions} +\section{Basic constructions}% \label{sec:basic-constructions} \subsection{Homology}% @@ -301,8 +301,6 @@ structure of the metric space. \end{itemize} \end{defn} -%% TODO figure with examples of simplicial complexes - \begin{figure}[ht] \centering \begin{tikzpicture} @@ -529,7 +527,37 @@ in the evolution of the network over time. \section{Zigzag persistence}% \label{sec:zigzag-persistence} +The standard algorithm to compute persistent homology +(\autoref{sec:persistent-homology}) only works for filtrations which +are nested sequences of simplicial complexes: +\[ \cdots \subseteq K_{i-1} \subseteq K_i \subseteq K_{i+1} \subseteq + \cdots \] +When studying temporal networks, we have two possibilities: +\begin{itemize} +\item Create an independent filtration (e.g.\ WRCF) from each time + step. The issue is that the topological features will be completely + disconnected from the time dimension. +\item Create a filtration along the time dimension. The issue in this + case is that the sequence is no longer nested (except for additive + temporal networks, ie when edges are never deleted). +\end{itemize} + +The solution to consider the time dimension is provided by +\emph{zigzag persistence}~\cite{carlsson_zigzag_2009}, which allows to +compute persistence on alternating nested sequences: +\[ \cdots \supseteq K_{i-1} \subseteq K_i \supseteq K_{i+1} \subseteq + \cdots \] + +This sequence can in turn be computed from a temporal network by +computing the union of each pair of consecutive time steps, +constructing a alternating sequence. + +Zigzag persistence is a special case of the more general concept of +\emph{multi-parameter persistence}~\cite{carlsson_theory_2009}, where +filtrations can span across multiple parameters. + +%% Note about libraries implementing zigzag persistence: Dionysus \chapter{Persistent Homology for Machine Learning applications}% \label{cha:pers-homol-mach}