Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/23446
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dc.contributor.authorKUIJPERS, Bart-
dc.contributor.authorGomez, Leticia-
dc.contributor.authorVAISMAN, Alejandro-
dc.date.accessioned2017-04-06T14:35:34Z-
dc.date.available2017-04-06T14:35:34Z-
dc.date.issued2017-
dc.identifier.urihttp://hdl.handle.net/1942/23446-
dc.description.abstractIn current “Big Data” scenarios, graph databases are increasingly being used. Online Analytical Processing (OLAP) operations can expand the possibilities of graph analysis beyond the traditional graph-based computation. We propose a multidimensional data model for graph analysis, that considers basic graph data and background information in the form of dimension hierarchies. The graphs in our model are node- and edge-labelled directed multi-hypergraphs, called graphoids, which can be defined at several different levels of granularity, using the dimensions associated with them. In this paper we describe this model, and its associated basic OLAP operations.-
dc.language.isoen-
dc.subject.otherOLAP; Data Warehousing; Graph Database; Big Data; Graph Aggregation-
dc.titlePerforming OLAP over Graph Data-
dc.typeResearch Report-
local.format.pages5-
local.bibliographicCitation.jcatR2-
dc.description.notesIngediend bij de Alberto Mendelzon International Workshop on Foundations of Data Management (AMW 2017).-
local.type.specifiedResearch Report-
local.type.specifiedResearch Report-
item.contributorKUIJPERS, Bart-
item.contributorGomez, Leticia-
item.contributorVAISMAN, Alejandro-
item.accessRightsClosed Access-
item.fullcitationKUIJPERS, Bart; Gomez, Leticia & VAISMAN, Alejandro (2017) Performing OLAP over Graph Data.-
item.fulltextWith Fulltext-
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