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Investigative Data Mining: Mathematical Models for Analyzing, Visualizing and Destabilizing Terrorist Networks

von Nasrullah Memon

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[1.] Nm/Fragment 097 01 - Diskussion
Zuletzt bearbeitet: 2012-05-01 09:29:32 Hindemith
Borgatti 2002, Fragment, Gesichtet, Nm, SMWFragment, Schutzlevel sysop, Verschleierung

Typus
Verschleierung
Bearbeiter
Hindemith
Gesichtet
Untersuchte Arbeit:
Seite: 97, Zeilen: 1-8
Quelle: Borgatti_2002
Seite(n): 2, Zeilen: 15ff
[The natural graphical representation of an adjacency matrix is a] table, such as shown in Figure 3. 2.

[TABLE, same as in source but extended by one row and one column]

Figure 3.2. Adjacency matrix for graph in Figure 3.1.

Examining either Figure 3.1 or Figure 3.2, we can see that not every vertex is adjacent to every other. A graph in which all vertices are adjacent to all others is said to be complete. The extent to which a graph is complete is indicated by its density, which is defined as the number of edges divided by the number possible. If self-loops are excluded, then the number possible is n(n-1)/2. Hence the density of the graph in Figure 3.1 is 7/21 = 0.33.

The natural graphical representation of an adjacency matrix is a table, such as

shown in Figure 2.

[TABLE]

Figure 2. Adjacency matrix for graph in Figure 1.

Examining either Figure 1 or Figure 2, we can see that not every vertex is adjacent to every other. A graph in which all vertices are adjacent to all others is said to be complete. The extent to which a graph is complete is indicated by its density, which is defined as the number of edges divided by the number possible. If self-loops are excluded, then the number possible is n(n-1)/2. [...] Hence the density of the graph in Figure 1 is 6/15 = 0.40.

Anmerkungen

The source is not given anywhere in the thesis.

Sichter
(Hindemith), Bummelchen


[2.] Nm/Fragment 097 09 - Diskussion
Zuletzt bearbeitet: 2012-04-26 07:59:44 Fiesh
Brandes Erlebach 2005, Fragment, Gesichtet, Nm, SMWFragment, Schutzlevel sysop, Verschleierung

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Verschleierung
Bearbeiter
Hindemith
Gesichtet
Untersuchte Arbeit:
Seite: 97, Zeilen: 9-19
Quelle: Brandes_Erlebach_2005
Seite(n): 7, 8, Zeilen: p7: 30ff; p8: 1ff
Graphs can be undirected or directed. The adjacency matrix of an undirected graph (as shown in Figure 3.2) is symmetric. An undirected edge joining vertices is denoted by .

In directed graphs, each directed edge (arc) has an origin (tail) and a destination (head). An edge with origin is represented by an order pair . As a shorthand notation, an edge can also be denoted by . It is to note that, in a directed graph, is short for , while in an undirected graph, and are the same and both stands for . Graphs that can have directed as well undirected edges are called mixed graphs, but such graphs are encountered rarely.

Graphs can be undirected or directed. In undirected graphs, the order of the endvertices of an edge is immaterial. An undirected edge joining vertices is denoted by . In directed graphs, each directed edge (arc) has an origin (tail) and a destination (head). An edge with origin and destination is represented by an ordered pair . As a shorthand notation, an edge or can also be denoted by . In a directed graph, is short for , while in an undirected graph, and are the same and both stand for . [...]. Graphs that can have directed edges as well as undirected edges are called mixed graphs, but such graphs are encountered rarely [...]
Anmerkungen

The source is not mentioned anywhere in the thesis.

The definitions given here are certainly standard and don't need to be quoted. However, Nm uses for several passages the same wording as the source.

Note also that "An edge with origin is represented by an order pair " is a curious abbreviation of the statement "An edge with origin and destination is represented by an ordered pair " in the source.

Sichter
(Hindemith). WiseWoman



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