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Amity International Conference on Artificial Intelligence (AICAI)

作者： Jain, Rachna Taygi, Praney Sharma, Mayank Khatri, Sunil Kumar Amity Univ Uttar Pradesh Amity Inst Informat Technol Noida India

ISBN: (纸本)9781538693469

multidimensional databases are main source dataset for data analytics. They are designed to provide fast and efficient backend support. Efficient physical layer design of these data bases is foremost requirement. Efficiency of any storage system depends on the indexing system, which is measured in terms of time and space complexity of the indexing system. In this paper new dimension of accuracy is proposed which along with time and space which will be measure of efficiency for indexing system at physical level of multidimensional data base. Fault Tolerance capability of self-organizing neural network is used for mapping data at conceptual level to physical storage level. Results of the research are very exciting and can be used for further development of the similar techniques.

关键词： Self-organizing maps multidimensional databases Accuracy Time Complexity Space complexity

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The Added Value of OLAP Preferences in What-If Applications 11

The Added Value of OLAP Preferences in What-If Applications

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11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K) / 11th International Conference on Knowledge Discovery and Information Retrieval (KDIR)

作者： Carvalho, Mariana Belo, Orlando Univ Minho ALGORITMI R&D Ctr Sch Engn Dept Informat Campus Gualtar P-4710057 Braga Portugal

ISBN: (纸本)9789897583827

These days, enterprise managers involved with decision-making processes struggle with several problems related to market position or business reputation of their companies. Collecting data and retrieving high-quality set of information is one of the main priority tasks of enterprise managers involved in decision-making processes. To overcome the difficulties that may arise from market competitiveness and gain some kind of competitive advantage, it is important that these managers make the most of adequate tools in order to get the right set of highly refined information. What-If analysis can help managers getting the competitive advantage they need. It allows for simulating hypothetical scenarios and analyzing the consequences of specific changes without harming business activities. In this paper, we propose a hybridization methodology, which combines What-If analysis process with OLAP usage preferences, for optimizing decision processes. We present and discuss the integration of OLAP usage preferences in the conventional What-If analysis with a case example.

关键词： Business Intelligence What-If Analysis On-Line Analytical Processing Usage Preferences OLAP Mining multidimensional databases Hybrid Methodology Decision-making Process

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Aerodynamic database error filtering via SVD-like methods

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AEROSPACE SCIENCE AND TECHNOLOGY 2017年 65卷 62-77页

作者： Jarzabek, Artur A. Moreno, Ana I. Perales, Jose M. Vega, Jose M. Univ Politecn Madrid ETSI Aeronaut & Espacio Plaza Cardenal Cisneros 3 E-28040 Madrid Spain

A method is presented to filter out errors in multidimensional databases. The method does not require any a priori information about the nature of the errors, which need not be small, neither random, nor exhibit zero mean. Instead, they are only required to be relatively uncorrelated to the clean information contained in the database. The method presented is based on an improved multidimensional extension by the authors (2016) [21] of a seminal gappy reconstruction method, due to Everson and Sirovich (1995) [18], who developed a two-dimensional method, based on SVD, able to reconstruct lost information at known database positions. The improved gappy reconstruction method is evolved in this paper as an error filtering method in two steps, since it is adapted to first (a) identify the error locations in the database and then (b) reconstruct the information in these locations by treating the associated data as gappy data. The resulting method filters out O(1) errors in an efficient fashion, for both random and systematic errors. Also, the method performs well both when errors are concentrated and when they are spread along the database. The method is illustrated and tested in several toy model and aerodynamic databases, obtained by discretizing a transcendental function and CFD-calculating the pressure on the surface of a wing for varying values of the angle of attack. (C) 2017 Elsevier Masson SAS. All rights reserved.

关键词： Data analysis Error detection Error filtering High order SVD multidimensional databases Aerodynamic databases

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Taming Size and Cardinality of OLAP Data Cubes over Big Data 31st

Taming Size and Cardinality of OLAP Data Cubes over Big Data

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31st British International Conference on databases (BICOD)

作者： Cuzzocrea, Alfredo Moussa, Rim Laabidi, Achref Univ Trieste DIA Dept Trieste Italy ICAR CNR Trieste Italy Univ Carthage LaTICE ENI Carthage Carthage Tunisia Univ Carthage ENI Carthage Carthage Tunisia

ISBN: (纸本)9783319607955;9783319607948

In this paper, we provide three authoritative application scenarios of TPC-H*d. The latter is a suitable transformation of TPC-H benchmark. The three application scenarios are (i) OLAP cube calculus on top of columnar relational DBMS, (ii) parallel OLAP data cube processing and (iii) virtual OLAP data cube design. We assess the effectiveness and the efficiency of our proposal, using open source systems, namely, Mondrian ROLAP server and its OLAP4j driver, MySQL-row oriented relational database management system and MonetDB - a column-oriented relational database management system.

关键词： multidimensional databases Data warehousing Schema evolution Logical OLAP Design

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Conceiving Hybrid What-If Scenarios Based on Usage Preferences 3rd

Conceiving Hybrid What-If Scenarios Based on Usage Preferenc...

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3rd International Conference on Decision Support System Technology (ICDSST)

作者： Carvalho, Mariana Belo, Orlando Univ Minho Sch Engn Dept Informat ALGORITMI R&D Ctr P-4710057 Braga Portugal

ISBN: (纸本)9783319574875;9783319574868

Nowadays, enterprise managers involved with decision-making processes struggle with numerous problems related to market position or business reputation of their companies. Owning the right and high quality set of information is a crucial factor for developing business activities and gaining competitive advantages on business arenas. However, today retrieving information is not enough anymore. The possibility to simulate hypothetical scenarios without harming the business using What-If analysis tools and to retrieve highly refined information is an interesting way for achieving such business advantages. In a previous work, we introduced a hybridization model that combines What-If analysis and OLAP usage preferences, which helps filter the information and meet the users' needs and business requirements without losing data quality. The main advantage is to provide the user with a way to overcome the difficulties that arise when dealing with the conventional What-If analysis scenario process. In this paper, we show an application of this methodology using a sample database, and compare the results of a conventional What-if process and our methodology. We designed and developed a specific piece of software, which aims to discover the best recommendations for What-If analysis scenarios' parameters using OLAP usage preferences, which incorporates user experience in the definition and analysis of a target decision-making scenario.

关键词： What-If analysis On-Line analytical processing Usage preferences Analysis systems specification multidimensional databases

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Aerodynamic database reconstruction via gappy high order singular value decomposition

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AEROSPACE SCIENCE AND TECHNOLOGY 2016年 52卷 115-128页

作者： Moreno, Ana I. Jarzabek, Artur A. Perales, Jose M. Vega, Jose M. Univ Politecn Madrid ETSI Aeronaut Espacio Dept Aircraft & Spacecraft Plaza Cardenal Cisneros 3 Madrid 28040 Spain Univ Politecn Madrid ETSI Aeronaut Espacio Dept Aircraft & Spacecraft Aerosp Engn Plaza Cardenal Cisneros 3 Madrid 28040 Spain Univ Politecn Madrid ETSI Aeronaut Espacio Dept Appl Mathematics Appl Math Plaza Cardenal Cisneros 3 Madrid 28040 Spain

A method based on an iterative application of high order singular value decomposition is derived for the reconstruction of missing data in multidimensional databases. The method is inspired by a seminal gappy reconstruction method for two-dimensional databases invented by Everson and Sirovich (1995) [20] and improved by Beckers and Rixen (2003) [21] and Venturi and Karniadakis (2004) [22]. In addition, the method is adapted to treat both noisy and structured-but-non-rectangular databases. The method is calibrated and illustrated using a three-dimensional toy model database that is obtained by discretizing a transcendental function. The performance of the method is tested on three aerodynamic databases for the flow past a wing, one obtained by a semi-analytical method, and two resulting from computational fluid dynamics. (C) 2016 Elsevier Masson SAS. All rights reserved.

关键词： multidimensional databases Aerodynamic databases CFD databases Gappy reconstruction High order singular value decomposition Linear algebra

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Enriching What-If Scenarios with OLAP Usage Preferences 8

Enriching What-If Scenarios with OLAP Usage Preferences

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8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (KDIR)

作者： Carvalho, Mariana Belo, Orlando Univ Minho Sch Engn Dept Informat ALGORITMI R&D Ctr Campus Gualtar P-4710057 Braga Portugal

ISBN: (纸本)9789897582035

Nowadays, enterprise managers involved in decision-making processes struggle with numerous problems related to market position or business reputation of their companies. Owning the right and high quality set of information is a crucial factor for developing business activities and consequently gaining competitive advantages on business arenas. However, retrieving information is not enough. The possibility to simulate hypothetical scenarios without harming the business using What-If analysis tools and to retrieve highly refined information is an interesting way of achieving such advantages. In this paper, we propose an approach for helping to optimize enterprise decision processes using What-If analysis scenarios combined with OLAP usage preferences. We designed and developed a specific piece of software, which aims to discover the best recommendations for What-If analysis scenarios' parameters using OLAP usage preferences, which incorporates user experience in the definition and analysis of a target decision-making scenario.

关键词： Business Intelligence What-If Analysis on-Line Analytical Processing Usage Preferences multidimensional databases

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Threshold-Based Distributed Continuous Top-k Query Processing for Minimizing Communication Overhead

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IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 2016年第2期E99D卷 383-396页

作者： Udomlamlert, Kamalas Hara, Takahiro Nishio, Shojiro Osaka Univ Grad Sch Informat Sci & Technol Suita Osaka 5650871 Japan

In this paper, we propose a communication-efficient top-k continuous query processing method on distributed local nodes where data are horizontally partitioned. A designated coordinator server takes the role of issuing queries from users to local nodes and delivering the results to users. The final results are requested via a top-k subscription which lets local nodes know which data and updates need to be returned to users. Our proposed method makes use of the active previously posed queries to identify a small set of needed top-k subscriptions. In addition, with the pre-indexed nodes' skylines, the number of local nodes to be subscribed can be significantly reduced. As a result, only a small number of subscriptions are informed to a small number of local nodes resulting in lower communication overhead. Furthermore, according to dynamic data updates, we also propose a method that prevents nodes from reporting needless updates and also maintenance procedures to preserve the consistency. The results of experiments that measure the volume of transferred data show that our proposed method significantly outperforms the previously proposed methods.

关键词： top-k queries skyline queries continuous queries multidimensional databases distributed systems

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Data Warehouse State of the art and future challenges 4

Data Warehouse State of the art and future challenges

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International Conference on Cloud Computing Technologies and Applications (CloudTech)

作者： El Moukhi, Nawfal El Azami, Ikram Mouloudi, Aziz FSK Dept Comp Sci Kenitra Morocco

ISBN: (纸本)9781467381499

The evolution of the computer world and the proliferation of storage devices has led to an explosion of available information, so that made their exploitation difficult. In addition, it has been found that a large part of this data will not be stored or used;however, it constitutes a precious raw material to understand the activity and anticipate its evolution. To cope with these problems, professionals implemented a decision making support systems (or decision support systems) and which allow a synthetic and multidimensional treatment of all available and stored information, hence the birth of the data warehouse and data mining techniques. This paper introduces the data warehousing, gives researchers terminologies necessary for understanding the process, and summarizes its evolution. It also presents an analysis of the latest research in the field, and explores the future trends. And therefore, this study provides a reference for researchers wishing to contribute in this area.

关键词： Business intelligence Data Warehouse Data Mining multidimensional databases OLAP

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On-demand multidimensional data integration: toward a semantic foundation for cloud intelligence

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JOURNAL OF SUPERCOMPUTING 2013年第1期65卷 217-257页

作者： Pedersen, Torben Bach Pedersen, Dennis Riis, Karsten Systemat Software Engn Aarhus Denmark Dynaway Aalborg Denmark

Cloud intelligence is a collection of technologies emerging from the migration of business intelligence and analytics technologies to a cloud computing environment combined with exploiting the massive range of new intelligence opportunities opened up by cloud computing. Cloud computing introduces several trends which require traditional business intelligence techniques to be re-thought, including agility, the ability to assemble resources, e.g., data sources, on-demand, and virtualization, e.g., that data are provided as a service over the web rather than stored in local databases. This paper focuses on the combination of data source agility and data-as-a-service virtualization and its use for cloud intelligence. After presenting the novel vision of the Cloud Warehouse, the paper goes on to present a comprehensive semantic foundation for on-demand multidimensional data integration, including formal data models, a range of query operators and re-write rules for optimization. This semantic foundation provides a sound formal basis for on-demand multidimensional data integration, which is a cornerstone of cloud intelligence.

关键词： Data integration multidimensional databases OLAP Federated databases Cloud intelligence

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