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CUBE File: A File Structure for Hierarchically Clustered OLAP Cubes [chapter]

Nikos Karayannidis, Timos Sellis, Yannis Kouvaras
2004 Lecture Notes in Computer Science  
Our results show that the CUBE File outperforms the most effective method proposed up to now for hierarchically clustering the cube, resulting in 7-9 times less I/Os on average for all workloads tested  ...  The CUBE File achieves hierarchical clustering of the data, enabling fast access via hierarchical restrictions.  ...  Acknowledgements We wish to thank Transaction Software GmbH for providing us Transbase Hypercube to run the UB-tree/MHC experiments.  ... 
doi:10.1007/978-3-540-24741-8_36 fatcat:ujpbpl5vorfajfp3ei757nujci

OLAP over Continuous Domains via Density-Based Hierarchical Clustering [chapter]

Michelangelo Ceci, Alfredo Cuzzocrea, Donato Malerba
2011 Lecture Notes in Computer Science  
hierarchical clustering algorithm.  ...  A clear advantage of this emerging approach is that of avoiding the beforehand definition of an ad-hoc discretization hierarchy along each OLAP dimension.  ...  This work is partial fulfillment of the research objective of ATENEO-2009 project "Estrazione, Rappresentazione e Analisi di Dati Complessi".  ... 
doi:10.1007/978-3-642-23863-5_57 fatcat:wd2kwi24ffdhhamohe4ozu2giq

A Data Mining-Based OLAP Aggregation of Complex Data

Riadh Ben Messaoud, Omar Boussaid, Sabine Loudcher Rabaséda
2006 International Journal of Data Warehousing and Mining  
We provide a generalized OLAP operator, called OpAC, based on the AHC. OpAC is adapted for all types of data since it deals with data cubes modelled within XML.  ...  For example, a user wants to observe the sum of sales amount of products according to years and regions.  ...  ., 2004 ) the interest of applying our approach on a cube of images files, and we have proven the semantic significance of its facts' aggregates.  ... 
doi:10.4018/jdwm.2006100101 fatcat:ok34fyhiknfgldkzujes7w45dm

Data mining techniques application for prediction in OLAP cube

Asma Lamani, Brahim Erraha, Malika Elkyal, Abdallah Sair
2019 International Journal of Electrical and Computer Engineering (IJECE)  
In the continuity of the work treating the coupling between the online analysis and data mining to integrate prediction into OLAP, an approach based on automatic learning with Clustering is proposed in  ...  The technique of data mining by regression trees is then applied for each sub-cube to predict the value of a cell.  ...  clustering and partitioning OLAP cubes.  ... 
doi:10.11591/ijece.v9i3.pp2094-2102 fatcat:tyhwn5fomraohfruddjgekxkti

OLAP on sequence data

Eric Lo, Ben Kao, Wai-Shing Ho, Sau Dan Lee, Chun Kit Chui, David W. Cheung
2008 Proceedings of the 2008 ACM SIGMOD international conference on Management of data - SIGMOD '08  
In this paper, we propose the concept of Sequence OLAP, or S-OLAP for short.  ...  This paper studies many aspects related to Sequence OLAP. The concepts of sequence cuboid and sequence data cube are introduced.  ...  We thank Jiawei Han, Foris Lee and the anonymous reviewers for their valuable comments.  ... 
doi:10.1145/1376616.1376682 dblp:conf/sigmod/LoKHLCC08 fatcat:5rkqrwekhfgnnop3y67oyqes2e

OLAP and statistical databases

Arie Shoshani
1997 Proceedings of the sixteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems - PODS '97  
Examples of SDBs and OLAP Databases We describe in this section an example of the traditional 2dimensional (2-D) representation of SDBs, followed by a data cube representation of OLAP databases, and show  ...  Tn the 1990's the area of On-Line-Analytic Processing (OLAP) was introduced for the analysis of transaction based business data, such as retail stores transactions.  ...  Acknowledgment This work is supported by the of Energy Research, U.S. Department of Energy under Contract DE-AC03-76SF00098.  ... 
doi:10.1145/263661.263682 dblp:conf/pods/Shoshani97 fatcat:nnwnpitmufdazda7yjhdk3pl4y

SISYPHUS: The implementation of a chunk-based storage manager for OLAP data cubes

Nikos Karayannidis, Timos Sellis
2003 Data & Knowledge Engineering  
In this article, we present the design and implementation of SISYPHUS, a storage manager for data cubes that provides an efficient physical base for performing OLAP operations.  ...  The SISYPHUS storage manager is based on a chunk-based data model that enables the hierarchical clustering of data with a very low storage cost.  ...  Acknowledgements This work has been partially funded by the European Union's Information Society Technologies Programme (IST) under project EDITH (IST-1999-20722). References  ... 
doi:10.1016/s0169-023x(02)00178-7 fatcat:ap4s3dwuprgedc5ph4nzgqvlvu

A knowledge-based framework for a mobile OLAP system

Nachida Rezoug, Omar Boussaid, Fahima Nader
2015 International Journal of Decision Support Systems  
We propose in this paper a knowledge-based framework for a mobile OLAP. Its main goal is to allow decision-makers to, efficiently, access datasets in OLAP system anywhere and anytime.  ...  This paper is a revised and expanded version of a paper entitled 'A contextual personalized recommender system for mobile OLAP' presented at the Information Technology and E-service (ICITes), Sousse, Tunis  ...  To extract this second knowledge (profile), we divide a log file of OLAP server to a set of clusters. Each cluster constitutes one profile.  ... 
doi:10.1504/ijdss.2015.067276 fatcat:d2oshgn4urcxbc5th3mhusvj2u

From Analysis to Interactive Exploration: Building Visual Hierarchies from OLAP Cubes [chapter]

Svetlana Vinnik, Florian Mansmann
2006 Lecture Notes in Computer Science  
We present a novel framework for comprehensive exploration of OLAP data by means of user-defined dynamic hierarchical visualizations.  ...  The multidimensional data model behind the OLAP architecture is particularly suitable for sophisticated analysis of large data volumes.  ...  Designing the Navigational Framework Probably the most popular paradigm underlying the OLAP navigation structure is that of a file browser, with each cube as a folder containing the list of top-level dimensions  ... 
doi:10.1007/11687238_31 fatcat:afih6apckrfslhqp4xzszw7bue

Semantic Metadata for Supporting Exploratory OLAP [article]

Jovan Varga
2016 Ph.d.-serien for Det Teknisk-Naturvidenskabelige Fakultet, Aalborg Universitet  
This research has been funded by the European Commission through the Erasmus Mundus Joint Doctorate "Information Technologies for Business Intelligence -Doctoral College" (IT4BI-DC) and it has been partly  ...  Acknowledgments This research has been funded by the European Commission through the Erasmus Mundus Joint Doctorate "Information Technologies for Business Intelligence -Doctoral College" (IT4BI-DC) and  ...  In the figure, Mary explores the dimensional cube data by clustering the instances according to their level value.  ... 
doi:10.5278/ fatcat:2jvgnvvmznh7dk7dap2aipiiii

Augmenting OLAP exploration with dynamic advanced analytics

Benjamin Leonhardi, Bernhard Mitschang, Rubén Pulido, Christoph Sieb, Michael Wurst
2010 Proceedings of the 13th International Conference on Extending Database Technology - EDBT '10  
These approaches support, however, only the creation of global dimensions that are not interactive for the user running the report.  ...  Online Analytical Processing (OLAP) is a popular technique for explorative data analysis.  ...  It uses Agglomerative Hierarchical Clustering to achieve a semantic aggregation on the attributes of a data cube dimension.  ... 
doi:10.1145/1739041.1739127 dblp:conf/edbt/LeonhardiMPSW10 fatcat:vcamhjkxzfadreeoaruruqvqpa

Integrating OLAP and Ranking: The Ranking-Cube Methodology

Dong Xin, Jiawei Han
2007 2007 IEEE 23rd International Conference on Data Engineering Workshop  
While pre-computation and multi-dimensional aggregation is the standard solution for OLAP, materializing dynamic ranking results is unrealistic because the ranking criteria are not known until the query  ...  Our performance studies show that ranking-cube is orders of magnitude faster than previous approaches. iii To my daughter Karen, my wife Xu and my parents. iv Acknowledgments This thesis would not have  ...  The hierarchical partition based version is implemented directly on file systems, and we use R-tree and B-trees to index the ranking cube and data.  ... 
doi:10.1109/icdew.2007.4401000 dblp:conf/icde/XinH07 fatcat:fxeo53c2lzco7jwqaslwcigqi4

Can we analyze big data inside a DBMS?

Carlos Ordonez
2013 Proceedings of the sixteenth international workshop on Data warehousing and OLAP - DOLAP '13  
, being the main technology for big data analytics.  ...  Such large-scale systems are mostly based on the Hadoop distributed file system and MapReduce.  ...  Clustering is commonly used as a building block for more complex models. Techniques that have been incorporated internally in a DBMS include K-means clustering and hierarchical clustering.  ... 
doi:10.1145/2513190.2513198 dblp:conf/dolap/Ordonez13 fatcat:ejuvzywvqrd5jig6bfcmixc66m

An Effective Method to Answer OLAP Queries using R*-trees in Distributed Environment

F. SagayarajFrancis, P. Xavier
2014 International Journal of Computer Applications  
Evaluation of OLAP queries is one of the challenging tasks in a database system. Attempts are being continuously made to improve the efficiency of the methods that answer OLAP queries.  ...  Experimental evaluation gives improved results due to the proposed method.  ...  Fig 7: A sample aR-tree A recent approach that has been reported in the literature for a cloud based real-time OLAP system uses the distributed PDCR tree [10] .  ... 
doi:10.5120/18859-0474 fatcat:3ypmmh6xanddngz426xldesevm

Effectively and efficiently supporting roll-up and drill-down OLAP operations over continuous dimensions via hierarchical clustering

Michelangelo Ceci, Alfredo Cuzzocrea, Donato Malerba
2013 Journal of Intelligent Information Systems  
Following this research trend, in this paper we propose a novel method, founded on a density-based hierarchical clustering algorithm, to support roll-up and drill-down operations over OLAP data cubes with  ...  The method hierarchically clusters dimension instances by also taking fact-table measures into account. Thus, we enhance the clustering effect with respect to the possible analysis.  ...  Acknowledgements The authors thank Lynn Rudd for reading through the paper.  ... 
doi:10.1007/s10844-013-0268-1 fatcat:cnjmsppqbzfh3kh4q5xbrn2fte
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