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Analyzing and adapting graph algorithms for large persistent graphs
Linköping University, Department of Computer and Information Science.
2008 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

In this work, the graph database Neo4j developed by Neo Technology is presented together with some of it's functionality when it comes to accessing data as a graph. This type of data access brings the possibility to implement common graph algorithms on top of Neo4j. Examples of such algorithms are presented together with their theoretical backgrounds. These are mainly algorithms for finding shortest paths and algorithms for different graph measures such as centrality measures. The implementations that have been made are presented, as well as complexity analysis and the performance measures performed on them. The conclusions include that Neo4j is well suited for these types of implementations.

Place, publisher, year, edition, pages
2008. , p. 70
Keywords [en]
graph, database, algorithm
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:liu:diva-15422ISRN: LIU-IDA/LITH-EX-A--08/048--SEOAI: oai:DiVA.org:liu-15422DiVA, id: diva2:114159
Subject / course
Computer science (20-credit final thesis, D level)
Presentation
2008-10-30, Alan Turing, IDA, 13:15 (Swedish)
Uppsok
Technology
Examiners
Available from: 2008-11-07 Created: 2008-11-06 Last updated: 2018-01-13Bibliographically approved

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf