The hierarchical agglomerative clustering with Gower index: A methodology for automatic design of OLAP cube in ecological data processing context

Sautot, Lucile; Faivre, Bruno; Journaux, Ludovic; Molin, Paul

doi:10.1016/j.ecoinf.2014.07.011

Cited by 16 publications

(18 citation statements)

References 14 publications

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“…For that reasons, some works investigate definition of hierarchies by means of Data Mining (DM) algorithms (Favre et al, 2006;Sautot et al, 2014b). However, this design step is applied once the multidimensional model has been defined, and it takes into account only members of one dimension.…”

Section: Introductionmentioning

confidence: 99%

“…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 paper we propose a new mixed refinement design methodology where the classical data-driven approach is enhanced with data mining to create new dimensions hierarchies.…”

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confidence: 99%

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Mixed Driven Refinement Design of Multidimensional Models based on Agglomerative Hierarchical Clustering

Sautot

Bimonte²,

Journaux

et al. 2015

Proceedings of the 17th International Conference on Enterprise Information Systems

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Abstract: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 paper we propose a new mixed refinement design methodology where the classical data-driven approach is enhanced with data mining to create new dimensions hierarchies. A tool implementing our approach is also presented to validate our theoretical proposal.

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Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

Mixed Driven Refinement Design of Multidimensional Models based on Agglomerative Hierarchical Clustering

Sautot

Bimonte²,

Journaux

et al. 2015

Proceedings of the 17th International Conference on Enterprise Information Systems

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“…when all the variables were taken simultaneously. According to another sorting criterion methods of agglomerative hierarchical clustering were used (Sautot et al 2015). This means that the first cluster is formed of two objects on the basis of a matrix of (dis)similarity.…”

Section: Discussionmentioning

confidence: 99%

Statistical analysis of factors influencing the results of enterprises in dairy industry

Náglová¹,

Boberova²,

Horáková³

et al. 2017

Agric. Econ. - Czech

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Th e article deals with companies processing and producing dairy products and cheeses in the Czech market. Th e dairy industry is a crucial fi eld among the production of food products. On March 31, 2015 the milk quotas were cancelled. Th e impacts of their cancelation can bring danger for the dairy business but also provide some opportunities. Th erefore it is important that businesses are economically powerful and so are able to strengthen their competitive position. Th is article aims to analyse businesses to identify vulnerable groups of businesses and those groups whose welfare is not essentially jeopardized. Partially, the aim is to assess whether there are signifi cant diff erences in economic indicators among enterprises of the dairy industry (divided according to their size, ownership and subsidy drawing). At the same time the aim is to fi nd groups of dairy businesses from the set which are similar to each other and which diff er from other groups of companies and thus set their position in the Czech market. Over all there were 35 dairy milk businesses analysed in 2013. Th ere were statistically signifi cant diff erences in some economic indicators among corporations considering drawing grants, size, ownership structure and binding to primary production. According to the cluster analysis the large companies with foreign ownership can be considered as a potential threat and may aff ect the position and competitiveness of other businesses. Th e results indicate the endangered position of Czech medium-sized businesses as well as opportunities for stabilizing small businesses which specialize closely.

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“…In particular, (i) we present an extension of the UML profile for spatial DW integrating the Hierarchical Agglomerative Clustering for defining dimension hierarchies [17], we (ii) extend the prototyping methodology and (iii) tool to handle with DM setting, and (iii) we validate our approach on a real data set concerning bird biodiversity.…”

Section: Introductionmentioning

confidence: 99%

“…Some work about the integration of Data Mining (DM) and OLAP systems has been done to enhance OLAP operators with mined indicators [8], and/or to define the DW schema [17,18]. In [8] classical OLAP operators (drill-down and roll-up operations, slicing, dicing, pivoting) are completed by analysis operators based on DM algorithms.…”

Section: Introductionmentioning

confidence: 99%

A Methodology and Tool for Rapid Prototyping of Data Warehouses Using Data Mining: Application to Birds Biodiversity

Sautot

Bimonte²,

Journaux

et al. 2014

Model and Data Engineering

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The hierarchical agglomerative clustering with Gower index: A methodology for automatic design of OLAP cube in ecological data processing context

Cited by 16 publications

References 14 publications

Mixed Driven Refinement Design of Multidimensional Models based on Agglomerative Hierarchical Clustering

Mixed Driven Refinement Design of Multidimensional Models based on Agglomerative Hierarchical Clustering

Statistical analysis of factors influencing the results of enterprises in dairy industry

A Methodology and Tool for Rapid Prototyping of Data Warehouses Using Data Mining: Application to Birds Biodiversity

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