71 research outputs found
Personnalisation de SystÚmes OLAP Annotés
National audienceThis paper deals with personalization of annotated OLAP systems. Data constellation is extended to support annotations and user preferences. Annotations reflect the decision-maker experience whereas user preferences enable users to focus on the most interesting data. User preferences allow annotated contextual recommendations helping the decision-maker during his/her multidimensional navigations
Conception assistĂ©e dâentrepĂŽts de donnĂ©es et de documents XML pour lâanalyse OLAP
Aujourdâhui, les entrepĂŽts de donnĂ©es constituent un enjeu majeur pour les applications dĂ©cisionnelles au sein des entreprises. Les sources dâun entrepĂŽt, câest Ă dire lâorigine des donnĂ©es qui lâalimentent, sont diverses et hĂ©tĂ©rogĂšnes : fichiers sĂ©quentiels, feuilles de tableur, bases de donnĂ©es relationnelles, documents du Web. La complexitĂ© est telle que les logiciels du marchĂ© ne rĂ©pondent que partiellement aux attentes des dĂ©cideurs lorsque ceux-ci souhaitent analyser les donnĂ©es. Nos travaux sâinscrivent donc dans le contexte des systĂšmes dĂ©cisionnels qui intĂšgrent tous types de donnĂ©es (principalement extraites de bases de donnĂ©es relationnelles et de bases de documents XML) et qui sont destinĂ©s Ă des dĂ©cideurs. Ils visent Ă proposer des modĂšles, des mĂ©thodes et des outils logiciels pour Ă©laborer et manipuler des entrepĂŽts de donnĂ©es. Nos travaux ont plus prĂ©cisĂ©ment portĂ© sur deux problĂ©matiques complĂ©mentaires : lâĂ©laboration assistĂ©e dâun entrepĂŽt de donnĂ©es ainsi que la modĂ©lisation et lâanalyse OLAP de documents XML.Today, data warehouses are a major issue for business intelligence applications within companies. Sources of a warehouse, i.e. the origin of data that feed, are diverse and heterogeneous sequential files, spreadsheets, relational databases, Web documents. The complexity is such that the software on the market only partially meets the needs of decision makers when they want to analyze the data. Therefore, our work is within the decision support systems context that integrate all data types (mainly extracted from relational databases and XML documents databases) for decision makers. They aim to provide models, methods and software tools to elaborate and manipulate data warehouses. Our work has specifically focused on two complementary issues: aided data warehouse and modeling and OLAP analysis of XML documents
Conception assistĂ©e dâentrepĂŽts de donnĂ©es et de documents XML pour lâanalyse OLAP
Aujourdâhui, les entrepĂŽts de donnĂ©es constituent un enjeu majeur pour les applications dĂ©cisionnelles au sein des entreprises. Les sources dâun entrepĂŽt, câest Ă dire lâorigine des donnĂ©es qui lâalimentent, sont diverses et hĂ©tĂ©rogĂšnes : fichiers sĂ©quentiels, feuilles de tableur, bases de donnĂ©es relationnelles, documents du Web. La complexitĂ© est telle que les logiciels du marchĂ© ne rĂ©pondent que partiellement aux attentes des dĂ©cideurs lorsque ceux-ci souhaitent analyser les donnĂ©es. Nos travaux sâinscrivent donc dans le contexte des systĂšmes dĂ©cisionnels qui intĂšgrent tous types de donnĂ©es (principalement extraites de bases de donnĂ©es relationnelles et de bases de documents XML) et qui sont destinĂ©s Ă des dĂ©cideurs. Ils visent Ă proposer des modĂšles, des mĂ©thodes et des outils logiciels pour Ă©laborer et manipuler des entrepĂŽts de donnĂ©es. Nos travaux ont plus prĂ©cisĂ©ment portĂ© sur deux problĂ©matiques complĂ©mentaires : lâĂ©laboration assistĂ©e dâun entrepĂŽt de donnĂ©es ainsi que la modĂ©lisation et lâanalyse OLAP de documents XML.Today, data warehouses are a major issue for business intelligence applications within companies. Sources of a warehouse, i.e. the origin of data that feed, are diverse and heterogeneous sequential files, spreadsheets, relational databases, Web documents. The complexity is such that the software on the market only partially meets the needs of decision makers when they want to analyze the data. Therefore, our work is within the decision support systems context that integrate all data types (mainly extracted from relational databases and XML documents databases) for decision makers. They aim to provide models, methods and software tools to elaborate and manipulate data warehouses. Our work has specifically focused on two complementary issues: aided data warehouse and modeling and OLAP analysis of XML documents
Conception assistée d'entrepÎts de données et de documents XML pour l'analyse OLAP
Aujourd hui, les entrepÎts de données constituent un enjeu majeur pour les applications décisionnelles au sein des entreprises. Les sources d un entrepÎt, c est à dire l origine des données qui l alimentent, sont diverses et hétérogÚnes : fichiers séquentiels, feuilles de tableur, bases de données relationnelles, documents du Web. La complexité est telle que les logiciels du marché ne répondent que partiellement aux attentes des décideurs lorsque ceux-ci souhaitent analyser les données. Nos travaux s inscrivent donc dans le contexte des systÚmes décisionnels qui intÚgrent tous types de données (principalement extraites de bases de données relationnelles et de bases de documents XML) et qui sont destinés à des décideurs. Ils visent à proposer des modÚles, des méthodes et des outils logiciels pour élaborer et manipuler des entrepÎts de données. Nos travaux ont plus précisément porté sur deux problématiques complémentaires : l élaboration assistée d un entrepÎt de données ainsi que la modélisation et l analyse OLAP de documents XML.Today, data warehouses are a major issue for business intelligence applications within companies. Sources of a warehouse, i.e. the origin of data that feed, are diverse and heterogeneous sequential files, spreadsheets, relational databases, Web documents. The complexity is such that the software on the market only partially meets the needs of decision makers when they want to analyze the data. Therefore, our work is within the decision support systems context that integrate all data types (mainly extracted from relational databases and XML documents databases) for decision makers. They aim to provide models, methods and software tools to elaborate and manipulate data warehouses. Our work has specifically focused on two complementary issues: aided data warehouse and modeling and OLAP analysis of XML documents.TOULOUSE1-SCD-Bib. electronique (315559902) / SudocSudocFranceF
Analyse multigraduelle OLAP
National audienceDecisional systems are based on multidimensional databases improving OLAP analyses. The paper describes a new OLAP operator named « BLEND » to perform multigradual analyses. The operation transforms multidimensional structures during querying in order to analyse measures according to various granularity levels, which are reorganised into a single parameter. We study valid combinations of the operation in the context of strict hierarchies. First experimentations implement the operation in an R-OLAP framework showing the slight cost of this operation
Ressources et parcours pour l'apprentissage du langage Python : aide à la navigation individualisée dans un hypermédia épistémique à partir de traces
This research work mainly concerns means of assistance in individualized navigation through an epistemic hypermedia. We have a number of resources that can be formalized by a directed acyclic graph (DAG) called the graph of epistemes. After identifying resources and pathways environments, methods of visualization and navigation, tracking, adaptation and data mining, we presented an approach correlating activities of design or editing with those dedicated to resourcesâ use and navigation. This provides ways of navigationâs individualization in an environment which aims to be evolutive. Then, we built prototypes to test the graph of epistemes. One of these prototypes was integrated into an existing platform. This epistemic hypermedia called HiPPY provides resources and pathways on Python language. It is based on a graph of epistemes, a dynamic navigation and a personalized knowledge diagnosis. This prototype, which was experimented, gave us the opportunity to evaluate the introduced principles and analyze certain uses.Les travaux de recherche de cette thĂšse concernent principalement lâaide Ă la navigation individualisĂ©e dans un hypermĂ©dia Ă©pistĂ©mique. Nous disposons dâun certain nombre de ressources qui peut se formaliser Ă lâaide dâun graphe acyclique orientĂ© (DAG) : le graphe des Ă©pistĂšmes. AprĂšs avoir cernĂ© les environnements de ressources et de parcours, les modalitĂ©s de visualisation et de navigation, de traçage, dâadaptation et de fouille de donnĂ©es, nous avons prĂ©sentĂ© une approche consistant Ă corrĂ©ler les activitĂ©s de conception ou dâĂ©dition Ă celles dĂ©diĂ©es Ă lâutilisation et la navigation dans les ressources. Cette approche a pour objectif de fournir des mĂ©canismes dâindividualisation de la navigation dans un environnement qui se veut Ă©volutif. Nous avons alors construit des prototypes appropriĂ©s pour mettre Ă lâĂ©preuve le graphe des Ă©pistĂšmes. Lâun de ces prototypes a Ă©tĂ© intĂ©grĂ© Ă une plateforme existante. Cet hypermĂ©dia Ă©pistĂ©mique baptisĂ© HiPPY propose des ressources et des parcours portant sur lâapprentissage du langage Python. Il sâappuie sur un graphe des Ă©pistĂšmes, une navigation dynamique et un bilan de connaissances personnalisĂ©. Ce prototype a fait lâobjet dâune expĂ©rimentation qui nous a donnĂ© la possibilitĂ© dâĂ©valuer les principes introduits et dâanalyser certains usages
A Survey of UserCentric Data Warehouses: From Personalization to Recommendationâ, The
ABSTRACT Providing a customized support for the OLAP brings tremendous challenges to the OLAP technology. Standing at the crossroads of the preferences and the data warehouse, two emerging trends are pointed out; namely: (i) the personalization and (ii) the recommendation. Although the panoply of the proposed approaches, the user-centric data warehouse community issues have not been addressed yet. In this paper we draw an overview of several user centric data warehouse proposals. We also discuss the two promising concepts in this issue, namely, the personalization and the recommendation of the data warehouses. We compare the current approaches among each others with respect to some criteria
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