1,900 research outputs found

    Data Mining

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    BCAS: A Web-enabled and GIS-based Decision Support System for the Diagnosis and Treatment of Breast Cancer

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    For decades, geographical variations in cancer rates have been observed but the precise determinants of such geographic differences in breast cancer development are unclear. Various statistical models have been proposed. Applications of these models, however, require that the data be assembled from a variety of sources, converted into the statistical models’ parameters and delivered effectively to researchers and policy makers. A web-enabled and GIS-based system can be developed to provide the needed functionality. This article overviews the conceptual web-enabled and GIS-based system (BCAS), illustrates the system’s use in diagnosing and treating breast cancer and examines the potential benefits and implications for breast cancer research and practice

    An Open Source Based Data Warehouse Architecture to Support Decision Making in the Tourism Sector

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    In this paper an alternative Tourism oriented Data Warehousing architecture is proposed which makes use of the most recent free and open source technologies like Java, Postgresql and XML. Such architecture's aim will be to support the decision making process and giving an integrated view of the whole Tourism reality in an established context (local, regional, national, etc.) without requesting big investments for getting the necessary software.Tourism, Data warehousing architecture

    Database Systems - Present and Future

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    The database systems have nowadays an increasingly important role in the knowledge-based society, in which computers have penetrated all fields of activity and the Internet tends to develop worldwide. In the current informatics context, the development of the applications with databases is the work of the specialists. Using databases, reach a database from various applications, and also some of related concepts, have become accessible to all categories of IT users. This paper aims to summarize the curricular area regarding the fundamental database systems issues, which are necessary in order to train specialists in economic informatics higher education. The database systems integrate and interfere with several informatics technologies and therefore are more difficult to understand and use. Thus, students should know already a set of minimum, mandatory concepts and their practical implementation: computer systems, programming techniques, programming languages, data structures. The article also presents the actual trends in the evolution of the database systems, in the context of economic informatics.database systems - DBS, database management systems – DBMS, database – DB, programming languages, data models, database design, relational database, object-oriented systems, distributed systems, advanced database systems

    Combining Objects with Rules to Represent Aggregation Knowledge in Data Warehouse and OLAP Systems

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    Les entrepĂŽts de donnĂ©es reposent sur la modĂ©lisation multidimensionnelle. A l'aide d'outils OLAP, les dĂ©cideurs analysent les donnĂ©es Ă  diffĂ©rents niveaux d'agrĂ©gation. Il est donc nĂ©cessaire de reprĂ©senter les connaissances d'agrĂ©gation dans les modĂšles conceptuels multidimensionnels, puis de les traduire dans les modĂšles logiques et physiques. Cependant, les modĂšles conceptuels multidimensionnels actuels reprĂ©sentent imparfaitement les connaissances d'agrĂ©gation, qui (1) ont une structure et une dynamique complexes et (2) sont fortement contextuelles. Afin de prendre en compte les caractĂ©ristiques de ces connaissances, nous proposons de les reprĂ©senter avec des objets (diagrammes de classes UML) et des rĂšgles en langage PRR (Production Rule Representation). Les connaissances d'agrĂ©gation statiques sont reprĂ©sentĂ©es dans les digrammes de classes, tandis que les rĂšgles reprĂ©sentent la dynamique (c'est-Ă -dire comment l'agrĂ©gation peut ĂȘtre effectuĂ©e en fonction du contexte). Nous prĂ©sentons les diagrammes de classes, ainsi qu'une typologie et des exemples de rĂšgles associĂ©es.AgrĂ©gation ; EntrepĂŽt de donnĂ©es ; ModĂšle conceptuel multidimensionnel ; OLAP ; RĂšgle de production ; UML

    Combining Objects with Rules to Represent Aggregation Knowledge in Data Warehouse and OLAP Systems

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    Data warehouses are based on multidimensional modeling. Using On-Line Analytical Processing (OLAP) tools, decision makers navigate through and analyze multidimensional data. Typically, users need to analyze data at different aggregation levels (using roll-up and drill-down functions). Therefore, aggregation knowledge should be adequately represented in conceptual multidimensional models, and mapped in subsequent logical and physical models. However, current conceptual multidimensional models poorly represent aggregation knowledge, which (1) has a complex structure and dynamics and (2) is highly contextual. In order to account for the characteristics of this knowledge, we propose to represent it with objects (UML class diagrams) and rules in Production Rule Representation (PRR) language. Static aggregation knowledge is represented in the class diagrams, while rules represent the dynamics (i.e. how aggregation may be performed depending on context). We present the class diagrams, and a typology and examples of associated rules. We argue that this representation of aggregation knowledge allows an early modeling of user requirements in a data warehouse project.Aggregation; Conceptual Multidimensional Model; Data Warehouse; On-line Analytical Processing (OLAP); Production Rule; UML
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