View Discovery in OLAP Databases through Statistical Combinatorial Optimization
Abstract
The capability of OLAP database software systems to handle data complexity comes at a high price for analysts, presenting them a combinatorially vast space of views of a relational database. We respond to the need to deploy technologies sufficient to allow users to guide themselves to areas of local structure by casting the space of ``views'' of an OLAP database as a combinatorial object of all projections and subsets, and ``view discovery'' as an search process over that lattice. We equip the view lattice with statistical information theoretical measures sufficient to support a combinatorial optimization process. We outline ``hop-chaining'' as a particular view discovery algorithm over this object, wherein users are guided across a permutation of the dimensions by searching for successive two-dimensional views, pushing seen dimensions into an increasingly large background filter in a ``spiraling'' search process. We illustrate this work in the context of data cubes recording summary statistics for radiation portal monitors at US ports.
- Authors:
- Publication Date:
- Research Org.:
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 971105
- Report Number(s):
- PNNL-SA-64183
400904120; TRN: US201003%%569
- DOE Contract Number:
- AC05-76RL01830
- Resource Type:
- Conference
- Resource Relation:
- Conference: Proceedings of the 21st International Conference on Scientific and Statistical Database Management, Lecture Notes in Computer Science, 5566:37-55
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 36 MATERIALS SCIENCE; ALGORITHMS; CASTING; DIMENSIONS; MANAGEMENT; MONITORS; OPTIMIZATION; PRICES; RADIATIONS; STATISTICS; OLAP; knowledge discovery; data discovery; information theory.
Citation Formats
Joslyn, Cliff A, Burke, Edward J, and Critchlow, Terence J. View Discovery in OLAP Databases through Statistical Combinatorial Optimization. United States: N. p., 2009.
Web.
Joslyn, Cliff A, Burke, Edward J, & Critchlow, Terence J. View Discovery in OLAP Databases through Statistical Combinatorial Optimization. United States.
Joslyn, Cliff A, Burke, Edward J, and Critchlow, Terence J. 2009.
"View Discovery in OLAP Databases through Statistical Combinatorial Optimization". United States.
@article{osti_971105,
title = {View Discovery in OLAP Databases through Statistical Combinatorial Optimization},
author = {Joslyn, Cliff A and Burke, Edward J and Critchlow, Terence J},
abstractNote = {The capability of OLAP database software systems to handle data complexity comes at a high price for analysts, presenting them a combinatorially vast space of views of a relational database. We respond to the need to deploy technologies sufficient to allow users to guide themselves to areas of local structure by casting the space of ``views'' of an OLAP database as a combinatorial object of all projections and subsets, and ``view discovery'' as an search process over that lattice. We equip the view lattice with statistical information theoretical measures sufficient to support a combinatorial optimization process. We outline ``hop-chaining'' as a particular view discovery algorithm over this object, wherein users are guided across a permutation of the dimensions by searching for successive two-dimensional views, pushing seen dimensions into an increasingly large background filter in a ``spiraling'' search process. We illustrate this work in the context of data cubes recording summary statistics for radiation portal monitors at US ports.},
doi = {},
url = {https://www.osti.gov/biblio/971105},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Fri May 01 00:00:00 EDT 2009},
month = {Fri May 01 00:00:00 EDT 2009}
}