Partition semantics for incomplete information in relational databases
SIGMOD '88 Proceedings of the 1988 ACM SIGMOD international conference on Management of data
Implementing data cubes efficiently
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
An overview of data warehousing and OLAP technology
ACM SIGMOD Record
Approximate computation of multidimensional aggregates of sparse data using wavelets
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Bottom-up computation of sparse and Iceberg CUBE
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Compressed data cubes for OLAP aggregate query approximation on continuous dimensions
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient computation of Iceberg cubes with complex measures
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Formal Concept Analysis: Mathematical Foundations
Formal Concept Analysis: Mathematical Foundations
Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals
Data Mining and Knowledge Discovery
Discovering Frequent Closed Itemsets for Association Rules
ICDT '99 Proceedings of the 7th International Conference on Database Theory
Fast Computation of Sparse Datacubes
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Surfing Wavelets on Streams: One-Pass Summaries for Approximate Aggregate Queries
Proceedings of the 27th International Conference on Very Large Data Bases
Condensed Cube: An Efficient Approach to Reducing Data Cube Size
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Extracting semantics from data cubes using cube transversals and closures
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Selection of Views to Materialize in a Data Warehouse
IEEE Transactions on Knowledge and Data Engineering
Quotient cube: how to summarize the semantics of a data cube
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
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Datacubes are specially useful for answering efficiently queries on data warehouses. Nevertheless the amount of generated aggregated data is incomparably more voluminous than the initial data which is itself very large. Recently, research work has addressed the issue of a concise representation of datacubes in order to reduce their size. The approach presented in this paper fits in a similar trend. We propose a concise representation, called Partition Cube, based on the concept of partition and define an algorithm to compute it. Various experiments are performed in order to compare our approach with methods fitting in the same trend. This comparison relates to the efficiency of algorithms computing the representations, the main memory requirements, and the storage space which is necessary.