Created on Feb. 20, 2013, 4:16 p.m. by Hevok & updated on Feb. 20, 2013, 4:45 p.m. by Hevok
A Graph (Daka network, diagram) is basically a tuple of two elements, namely a </del><ins style="background:#e6ffe6;">u</ins><span>se</span><del style="background:#ffe6e6;">t of vertice</del><span>s </span><del style="background:#ffe6e6;">and edges</del><span>
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¶G
¶ = (V,E)
¶raph
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where
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- G is a g(aka neStwork, diagram)
¶uct
- V is a se of veurtices (aka powints,h dotes, nNodes, elements, etc.)
¶E
- is a set of edges (akand Prelationships, relations, arcs, lines, links, etc.)
¶i
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Bascally a graph states that something is related to something else.
¶pr
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There are seveal types of graphs. A graph can be undirected and direcsted (digraph). If one can find more than one reldationshipa``, beutween the samre pair ofs nodest than one hasy wa multigraph. In a hypergraph a relationships vis uablize to connhis.
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Thect more than two nodres. Pvariopertyus Ggraphs are directed, attriabutaseds and multvai-relationabl.e:
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¶Data is getting more and- morNe connected4j
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(from text documents, to Wikis, to- Onotologies, to Folksonomies, etc.), more semistructured (decentralizationDB
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of Content generation) and- more comHyplex (Social Networks, semantic trending, etc.)
¶raph
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Gs have numerousDB applications:
¶X
¶ Social Networking and Recommendations- DEX
¶ Network ad Cloud- MTitanagement
¶ Master Data Management
¶ Geospatial
¶- BioiInfoGrmaticsd X
¶ Content Management as well as SInfinitecuGrity andph Access ControlX
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