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dc.contributor.authorKalimurthy, Aravind
dc.date.accessioned2018-05-01T04:30:16Z
dc.date.available2018-05-01T04:30:16Z
dc.date.issued2017-12
dc.identifier.otherkalimurthy_aravind_201712_ms
dc.identifier.urihttp://purl.galileo.usg.edu/uga_etd/kalimurthy_aravind_201712_ms
dc.identifier.urihttp://hdl.handle.net/10724/37802
dc.description.abstractWith data exponentially increasing in almost all fields in today’s world, there comes the necessity of handling and querying the data efficiently. Recently, many graph databases have emerged to handle big data. This is traditionally done using regular query handling processes and subgraph isomorphism. In this research, we introduce edge labels into graph simulation algorithms, so that we can quickly query and filter graphs not only using the vertex labels but also using edge labels. We have also accommodated cardinality restrictions for edge labeled graphs that improves the quality of the search results. Query processing involves taking a query graph and trying to find its pattern in a larger data graph. We have added the capability to query the graph database using wildcards, regular expressions, and variables. This is done by replacing, in a query graph, one or more strings in edge labels with wildcards, regular expressions or variables. Experiments are done on very large graphs with up to 30 million edges.
dc.languageeng
dc.publisheruga
dc.rightspublic
dc.subjectGraph Database, Graph Simulation Algorithms, Edge Label, Cardinality, Query Processing, Widcard, Regular Expression
dc.titleAdapting graph simulation algorithms for graph database query processing
dc.typeThesis
dc.description.degreeMS
dc.description.departmentComputer Science
dc.description.majorComputer Science
dc.description.advisorJohn A. Miller
dc.description.committeeJohn A. Miller
dc.description.committeeLakshmish Ramaswamy
dc.description.committeeLiming Cai


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