ACM Transactions on Database Systems (TODS)
OLAP, relational, and multidimensional database systems
ACM SIGMOD Record
Range queries in OLAP data cubes
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Selectivity estimation in spatial databases
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
An adaptive query execution system for data integration
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Optimal histograms for hierarchical range queries (extended abstract)
PODS '00 Proceedings of the nineteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Efficient and extensible algorithms for multi query optimization
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
A framework for expressing and combining preferences
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Approximating multi-dimensional aggregate range queries over real attributes
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Data mining: concepts and techniques
Data mining: concepts and techniques
STHoles: a multidimensional workload-aware histogram
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Materialized view selection and maintenance using multi-query optimization
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Joint optimization of cost and coverage of query plans in data integration
Proceedings of the tenth international conference on Information and knowledge management
Wavelet synopses with error guarantees
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
On the Multiple-Query Optimization Problem
IEEE Transactions on Knowledge and Data Engineering
Overcoming Limitations of Sampling for Aggregation Queries
Proceedings of the 17th International Conference on Data Engineering
Computing Iceberg Queries Efficiently
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Histogram-Based Approximation of Set-Valued Query-Answers
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Selectivity Estimation Without the Attribute Value Independence Assumption
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Fast Approximate Answers to Aggregate Queries on a Data Cube
SSDBM '99 Proceedings of the 11th International Conference on Scientific and Statistical Database Management
Multi-query optimization for on-line analytical processing
Information Systems
An optimal and progressive algorithm for skyline queries
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Deterministic wavelet thresholding for maximum-error metrics
PODS '04 Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Efficient computation of multiple group by queries
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Simultaneous optimization of complex mining tasks with a knowledgeable cache
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Proceedings of the 8th ACM international workshop on Data warehousing and OLAP
Overcoming Limitations of Approximate Query Answering in OLAP
IDEAS '05 Proceedings of the 9th International Database Engineering & Application Symposium
Optimization of query streams using semantic prefetching
ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2004
A quad-tree based multiresolution approach for two-dimensional summary data
SSDBM '03 Proceedings of the 15th International Conference on Scientific and Statistical Database Management
Improving range-sum query evaluation on data cubes via polynomial approximation
Data & Knowledge Engineering
A framework to support multiple query optimization for complex mining tasks
MDM '05 Proceedings of the 6th international workshop on Multimedia data mining: mining integrated media and complex data
Accuracy Control in Compressed Multidimensional Data Cubes for Quality of Answer-based OLAP Tools
SSDBM '06 Proceedings of the 18th International Conference on Scientific and Statistical Database Management
Answering top-k queries with multi-dimensional selections: the ranking cube approach
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
State-slice: new paradigm of multi-query optimization of window-based stream queries
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Approximate range---sum query answering on data cubes with probabilistic guarantees
Journal of Intelligent Information Systems
Multi-objective query processing for database systems
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Multiple-Objective Compression of Data Cubes in Cooperative OLAP Environments
ADBIS '08 Proceedings of the 12th East European conference on Advances in Databases and Information Systems
Towards approximate SQL: infobright's approach
RSCTC'10 Proceedings of the 7th international conference on Rough sets and current trends in computing
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A novel top-down compression technique for data cubes is introduced and experimentally assessed in this paper. This technique considers the previously unrecognized case in which multiple Hierarchical Range Queries (HRQ), a very useful class of OLAP queries, must be evaluated against the target data cube simultaneously. This scenario makes traditional data cube compression techniques ineffective, as, contrarily to the aim of our work, these techniques take into consideration one constraint only (e.g., a given space bound). The result of our study consists in introducing an innovative multiple-objective OLAP computational paradigm, and a hierarchical multidimensional histogram, whose main benefit is meaningfully implementing an intermediate compression of the input data cube able to simultaneously accommodate an even large family of different-in-nature HRQ. A complementary contribution of our work is represented by a wide experimental evaluation of the query performance of our technique against both benchmark and real-life data cubes, also in comparison with state-of- the-art histogram-based compression techniques.