Hierarchical dwarfs for the rollup cube
DOLAP '03 Proceedings of the 6th ACM international workshop on Data warehousing and OLAP
Extracting semantics from data cubes using cube transversals and closures
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Range CUBE: Efficient Cube Computation by Exploiting Data Correlation
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Accessing multidimensional data through natural text-based user interactivity
WISICT '04 Proceedings of the winter international synposium on Information and communication technologies
Incremental maintenance of quotient cube for median
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Incremental maintenance of quotient cube based on Galois lattice
Journal of Computer Science and Technology
PrefixCube: prefix-sharing condensed data cube
Proceedings of the 7th ACM international workshop on Data warehousing and OLAP
The cgmCUBE project: Optimizing parallel data cube generation for ROLAP
Distributed and Parallel Databases
Semi-closed cube: an effective approach to trading off data cube size and query response time
Journal of Computer Science and Technology
Research in data warehouse modeling and design: dead or alive?
DOLAP '06 Proceedings of the 9th ACM international workshop on Data warehousing and OLAP
Computing Iceberg Cubes by Top-Down and Bottom-Up Integration: The StarCubing Approach
IEEE Transactions on Knowledge and Data Engineering
Progressive ranking of range aggregates
Data & Knowledge Engineering
Answering ad hoc aggregate queries from data streams using prefix aggregate trees
Knowledge and Information Systems
ROLAP implementations of the data cube
ACM Computing Surveys (CSUR)
PnP: sequential, external memory, and parallel iceberg cube computation
Distributed and Parallel Databases
Mining multiple-level fuzzy blocks from multidimensional data
Fuzzy Sets and Systems
Supporting the data cube lifecycle: the power of ROLAP
The VLDB Journal — The International Journal on Very Large Data Bases
A Summary Structure of Data Cube Preserving Semantics
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
Approximate Range-Sum Queries over Data Cubes Using Cosine Transform
DEXA '08 Proceedings of the 19th international conference on Database and Expert Systems Applications
FCLOS: A client-server architecture for mobile OLAP
Data & Knowledge Engineering
LCS-Hist: taming massive high-dimensional data cube compression
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Computing data cubes using exact sub-graph matching: the sequential MCG approach
Proceedings of the 2009 ACM symposium on Applied Computing
A Multiple Correspondence Analysis to Organize Data Cubes
Proceedings of the 2007 conference on Databases and Information Systems IV: Selected Papers from the Seventh International Baltic Conference DB&IS'2006
Closed Non Derivable Data Cubes Based on Non Derivable Minimal Generators
ADMA '09 Proceedings of the 5th International Conference on Advanced Data Mining and Applications
CCBitmaps: A Space-Time Efficient Index Structure for OLAP
ADMA '09 Proceedings of the 5th International Conference on Advanced Data Mining and Applications
Compressing multidimensional structures: a case study
ECC'09 Proceedings of the 3rd international conference on European computing conference
An efficient method for maintaining data cubes incrementally
Information Sciences: an International Journal
Revisiting the cube lifecycle in the presence of hierarchies
The VLDB Journal — The International Journal on Very Large Data Bases
Online querying of d-dimensional hierarchies
Journal of Parallel and Distributed Computing
Multidimensional cyclic graph approach: Representing a data cube without common sub-graphs
Information Sciences: an International Journal
Brown Dwarf: A fully-distributed, fault-tolerant data warehousing system
Journal of Parallel and Distributed Computing
MOLAP cube based on parallel scan algorithm
ADBIS'11 Proceedings of the 15th international conference on Advances in databases and information systems
Parallel data cubes on multi-core processors with multiple disks
Proceedings of the 2011 Conference of the Center for Advanced Studies on Collaborative Research
Ag-Tree: a novel structure for range queries in data warehouse environments
DASFAA'06 Proceedings of the 11th international conference on Database Systems for Advanced Applications
A parallel and distributed method for computing high dimensional MOLAP
NPC'05 Proceedings of the 2005 IFIP international conference on Network and Parallel Computing
Computing iceberg quotient cubes with bounding
DaWaK'06 Proceedings of the 8th international conference on Data Warehousing and Knowledge Discovery
PMC: select materialized cells in data cubes
DaWaK'05 Proceedings of the 7th international conference on Data Warehousing and Knowledge Discovery
Computing high dimensional MOLAP with parallel shell mini-cubes
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part I
Lossless reduction of datacubes
DEXA'06 Proceedings of the 17th international conference on Database and Expert Systems Applications
Using functional dependencies for reducing the size of a data cube
FoIKS'12 Proceedings of the 7th international conference on Foundations of Information and Knowledge Systems
A clustered Dwarf structure to speed up queries on data cubes
DaWaK'07 Proceedings of the 9th international conference on Data Warehousing and Knowledge Discovery
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Pre-computed data cube facilitates OLAP (On-Line Analytical Processing). It is a well-known fact that data cube computation is an expensive operation, which attracts a lot of attention. While most proposed algorithms devoted themselves to optimizing memory management and reducing computation costs, less work addresses one of the fundamental issues: the size of a data cube is huge when a large base relation with a large number of attributes is involved. In this paper, we propose a new concept, called a condensed data cube. The condensed cube is of much smaller size of a complete non-condensed cube. More importantly, it is a fully pre-computed cube without compression, and, hence, it requires neither decompression nor further aggregation when answering queries. Several algorithms for computing condensed cube are proposed. Results of experiments on the effectiveness of condensed data cube are presented, using both synthetic and real-world data . The results indicate that the proposed condensed cube can reduce both the cube size and therefore its computation time.