Search results for "analytical process"

showing 5 items of 15 documents

OLAP Personalization with User-Describing Profiles

2010

In this paper we have highlighted five existing approaches for introducing personalization in OLAP: preference constructors, dynamic personalization, visual OLAP, recommendations with user session analysis and recommendations with user profile analysis and have analyzed research papers within these directions. We have pointed out applicability of personalization to OLAP schema elements in these approaches. The comparative analysis has been made in order to highlight a certain personalization approach. A new method has been proposed, which provides exhaustive description of interaction between user and data warehouse, using the concept of Zachman Framework [1, 2], according to which a set of…

User profileData collectionInformation retrievalComputer scienceOnline analytical processingSchema (psychology)Zachman FrameworkData miningcomputer.software_genrecomputerData warehousePersonalization
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Towards Introducing User Preferences in OLAP Reporting Tool

2012

This paper presents an OLAP reporting tool and an approach for determining and processing user OLAP preferences, which are useful for generating recommendations on potentially interesting reports. We discuss the metadata layers of the reporting tool including our proposed OLAP preferences metamodel, which supports various scenarios of formulating preferences of two different types: schema-specific and report-specific. The process of semantic metadata usage at the stage of formulating user preferences is also considered. The methods for processing schema-specific and report-specific OLAP preferences are outlined.

World Wide WebMetadataInformation retrievalComputer scienceProcess (engineering)Online analytical processingInformationSystems_DATABASEMANAGEMENTData warehouseMetamodeling
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The Hierarchical Agglomerative Clustering with Gower index: a methodology for automatic design of OLAP cube in ecological data processing context

2015

In Press, Corrected Proof; International audience; The OLAP systems can be an improvement for ecological studies. In fact, ecology studies, follows and analyzes phenomenon across space and time and according to several parameters. OLAP systems can provide to ecologists browsing in a large dataset. One focus of the current research on OLAP system is the automatic design of OLAP cubes and of data warehouse schemas. This kind of works makes accessible OLAP technology to non information technology experts. But to be efficient, the automatic OLAP building must take into account various cases. Moreover the OLAP technology is based on the concept of hierarchy. Thereby the hierarchical clustering m…

[ INFO.INFO-NA ] Computer Science [cs]/Numerical Analysis [cs.NA]Computer scienceContext (language use)02 engineering and technologycomputer.software_genre020204 information systems0202 electrical engineering electronic engineering information engineeringDimension (data warehouse)Cluster analysisEcology Evolution Behavior and Systematics[ SDE.BE ] Environmental Sciences/Biodiversity and Ecology[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]OLAPEcologyAutomatic designApplied MathematicsEcological ModelingOnline analytical processing[ STAT.AP ] Statistics [stat]/Applications [stat.AP]InformationSystems_DATABASEMANAGEMENTHierarchical agglomerative clustering[INFO.INFO-NA]Computer Science [cs]/Numerical Analysis [cs.NA]Missing dataData warehouseComputer Science ApplicationsHierarchical clustering[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB]Computational Theory and MathematicsModeling and SimulationOLAP cube020201 artificial intelligence & image processingData mining[SDE.BE]Environmental Sciences/Biodiversity and EcologyBird populationcomputer
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Mixed Driven Refinement Design of Multidimensional Models based on Agglomerative Hierarchical Clustering

2015

20 pages; International audience; Data warehouses (DW) and OLAP systems are business intelligence technologies allowing the on-line analysis of huge volume of data according to users' needs. The success of DW projects essentially depends on the design phase where functional requirements meet data sources (mixed design methodology) (Phipps and Davis, 2002). However, when dealing with complex applications existing design methodologies seem inefficient since decision-makers define functional requirements that cannot be deduced from data sources (data driven approach) and/or they have not sufficient application domain knowledge (user driven approach) (Sautot et al., 2014b). Therefore, in this p…

[SDE] Environmental SciencesMultidimensional designData Warehouse[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingOLAPbusiness.industryComputer scienceOnline analytical processingCLUSTERING HIERARCHIQUEVolume (computing)Functional requirementcomputer.software_genreData warehouseData-driven[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingApplication domain[SDE]Environmental SciencesBusiness intelligenceData MiningData mining[SDE.BE]Environmental Sciences/Biodiversity and EcologybusinessDesign methodscomputerProceedings of the 17th International Conference on Enterprise Information Systems
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Formalization of scientific process and conceptual modelling for the study of territorial and products distribution dynamics (ArchaeDyn II programme)

2012

International audience; The ArchaeDyn team has investigated territorial dynamics by comparing areas over long time spans between the Neolithic and Modern times. Datasets on various themes have been shared and indicators and analytical models produced. This paper presents both the formalization of the scientific process used in the ArchaeDyn programme and a conceptual model of the systems and components so that synchronic and diachronic comparisons can be made. The aim is to clarify the transition from an archaeological feature (a site or an artefact) or a recording unit (survey area) as the input, to the characterization of spaces describing a system as the output. The approach is described…

[SHS.ARCHEO] Humanities and Social Sciences/Archaeology and Prehistory[SHS.STAT]Humanities and Social Sciences/Methods and statisticsformalization[SHS.ARCHEO]Humanities and Social Sciences/Archaeology and PrehistoryModelsconsumption areas[ SHS.ARCHEO ] Humanities and Social Sciences/Archaeology and Prehistoryagricultural areas[SHS.STAT] Humanities and Social Sciences/Methods and statisticssettlement patternsanalytical process[ SHS.STAT ] Humanities and Social Sciences/Methods and statistics
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