Architecting a Dimensional Document Warehouse

Schymik, Gregory; Corral, Karen; Schuff, David; StLouis, R.

doi:10.1109/hicss.2007.85

Cited by 5 publications

(6 citation statements)

References 3 publications

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“…A concept hierarchy characterizes a sequence of mapping from a set of low-level concepts to higher-level and more generalized concepts [28]. It allows data to be managed at multiple levels of abstraction.…”

Section: Concept Hierarchy and Olap Operationsmentioning

confidence: 99%

In-Depth Analysis of Energy Efficiency Related Factors in Commercial Buildings Using Data Cube and Association Rule Mining

et al. 2017

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Significant amounts of energy are consumed in the commercial building sector, resulting in various adverse environmental issues. To reduce energy consumption and improve energy efficiency in commercial buildings, it is necessary to develop effective methods for analyzing building energy use. In this study, we propose a data cube model combined with association rule mining for more flexible and detailed analysis of building energy consumption profiles using the Commercial Buildings Energy Consumption Survey (CBECS) dataset, which has accumulated over 6700 existing commercial buildings across the U.S.A. Based on the data cube model, a multidimensional commercial sector building energy analysis was performed based upon on-line analytical processing (OLAP) operations to assess the energy efficiency according to building factors with various levels of abstraction. Furthermore, the proposed analysis system provided useful information that represented a set of energy efficient combinations by applying the association rule mining method. We validated the feasibility and applicability of the proposed analysis model by structuring a building energy analysis system and applying it to different building types, weather conditions, composite materials, and heating/cooling systems of the multitude of commercial buildings classified in the CBECS dataset.

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Section: Concept Hierarchy and Olap Operationsmentioning

confidence: 99%

In-Depth Analysis of Energy Efficiency Related Factors in Commercial Buildings Using Data Cube and Association Rule Mining

et al. 2017

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“…Data warehouses and OLAP tools are based on a multidimensional data model. This model views data in the form of a data cube [23,24,[26][27][28][29]. A data cube allows data to be modeled and viewed in multiple dimensions.…”

Section: Multidimensional Data Cubementioning

confidence: 99%

“…A data warehouse requires a concise, subject-oriented schema that facilitates online data analysis. The most popular data model for a data warehouse is the multidimensional model [26][27][28][29][30][31]. In this paper, we used a star schema for the multidimensional analysis model.…”

Section: Multidimensional Data Cubementioning

confidence: 99%

“…A number of OLAP data cube operations exist to materialize these different views, allowing interactive querying and analysis of the data at hand. Hence OLAP provides a user-friendly environment for interactive data analysis [26][27][28][29][30][31], which makes it possible to construct a flexible and extensible analysis system.…”

Section: Concept Hierarchy and Olap Operationmentioning

confidence: 99%

“…A concept hierarchy defines a sequence of mappings from a set of low‐level concepts to higher‐level and more general concepts . Concept hierarchies allow data to be handled at varying levels of abstraction.…”

Section: Netcube: a Comprehensive Traffic Analysis Modelmentioning

confidence: 99%

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NetCube: a comprehensive network traffic analysis model based on multidimensional OLAP data cube

Park

et al. 2012

Int J Network Mgmt

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SUMMARY Network traffic monitoring and analysis are essential for effective network operation and resource management. In particular, multidimensional analysis for long‐term traffic data is necessary for comprehensive understanding of the traffic trend and effective quality‐of‐service provision considering the extremely dynamic behavior of the current Internet, where various types of traffic occur from high‐speed network links and greatly increasing number of applications. However, only limited analysis results are provided, as the existing network traffic analysis tools and systems are developed and deployed focusing on their own specialized analysis purposes. Consequently, it is difficult to understand the network comprehensively and deeply, which increases the necessity for multilateral analysis of long‐term traffic data. In this paper, we propose a novel traffic analysis model for large volumes of Internet traffic accumulated over a long period of time. The NetCube, the proposed network traffic analysis model using online analytical processing (OLAP) on a multidimensional data cube, provides an easy and fast way to construct a multidimensional traffic analysis system for comprehensive and detailed analysis of long‐term traffic data by utilizing simple OLAP operations and powerful data‐mining techniques on various abstraction levels of traffic data to complete the analysis purpose. We validate the feasibility and applicability of the proposed NetCube traffic analysis model by implementing a traffic analysis system and applying it to our campus network. Copyright © 2012 John Wiley & Sons, Ltd.

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Integrating visual and community environments in a motorcycle crash and casualty estimation

Kim,

Yeo,

Lim

et al. 2024

Accident Analysis & Prevention

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Architecting a Dimensional Document Warehouse

Cited by 5 publications

References 3 publications

In-Depth Analysis of Energy Efficiency Related Factors in Commercial Buildings Using Data Cube and Association Rule Mining

In-Depth Analysis of Energy Efficiency Related Factors in Commercial Buildings Using Data Cube and Association Rule Mining

NetCube: a comprehensive network traffic analysis model based on multidimensional OLAP data cube

Integrating visual and community environments in a motorcycle crash and casualty estimation

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