Analyzing and adapting graph algorithms for large persistent graphs
Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
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, pages
2008. , 70 p.
graph, database, algorithm
National CategoryComputer Science
IdentifiersURN: urn:nbn:se:liu:diva-15422ISRN: LIU-IDA/LITH-EX-A--08/048--SEOAI: oai:DiVA.org:liu-15422DiVA: diva2:114159
Subject / course
Computer science (20-credit final thesis, D level)
2008-10-30, Alan Turing, IDA, 13:15 (Swedish)