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
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
ACM Transactions on Information Systems (TOIS)
Journal of Intelligent Information Systems
Pattern Recognition Letters
Cubegrades: Generalizing Association Rules
Data Mining and Knowledge Discovery
Compressed data cube for approximate OLAP query processing
Journal of Computer Science and Technology
Discovery-Driven Exploration of OLAP Data Cubes
EDBT '98 Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology
ICICLES: Self-Tuning Samples for Approximate Query Answering
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Approximate query processing using wavelets
The VLDB Journal — The International Journal on Very Large Data Bases
Dynamic sample selection for approximate query processing
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Relation between PLSA and NMF and implications
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Using Datacube Aggregates for Approximate Querying and Deviation Detection
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
Probabilistic latent semantic analysis
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Flexible query answering in data cubes
DaWaK'05 Proceedings of the 7th international conference on Data Warehousing and Knowledge Discovery
What Can Formal Concept Analysis Do for Data Warehouses?
ICFCA '09 Proceedings of the 7th International Conference on Formal Concept Analysis
Probabilistic model for accuracy estimation in approximate monodimensional analyses
WSEAS Transactions on Computers
Accuracy estimation in approximate query processing
ICCOMP'10 Proceedings of the 14th WSEAS international conference on Computers: part of the 14th WSEAS CSCC multiconference - Volume II
Metrics for approximate query engine evaluation
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Towards intensional answers to OLAP queries for analytical sessions
Proceedings of the fifteenth international workshop on Data warehousing and OLAP
Hi-index | 0.00 |
Databases and data warehouses contain an overwhelming volume of information that users must wade through in order to extract valuable and actionable knowledge to supportthe decision-making process. This contribution addresses the problem of automatically analyzing large multidimensional tables to get a concise representation of data, identify patterns and provide approximate answers to queries. Since data cubes are nothing but multi-way tables, we propose to analyze the potential of a probabilistic modeling technique, called non-negative multi-way array factorization, for approximating aggregate and multidimensional values. Using such a technique, we compute the set of components (clusters) that best fit the initial data set and whose superposition approximates the original data. The generated components can then be exploited for approximately answering OLAP queries such as roll-up, slice and dice operations. The proposed modeling technique will then be compared against the log-linear modeling technique which has already been used in the literature for compression and outlier detection in data cubes. Finally, three data sets will be used to discuss the potential benefits of non-negative multiway array factorization.